Q3 2024 MongoDB Inc Earnings Call

Speaker 1: Thank you for standing by and welcome to MongoDB's Q3 fiscal year 24 conference.

Thank you for standing by and welcome to Mongo DB Q3 fiscal year 'twenty for a conference call. At this time all participants are in a listen only mode.

Speaker 1: At this time, all participants are in a small mode. After the speakers presentations, there'll be a question and answer session. To ask the question at that time, please press start.

After the Speakers' presentation there'll be a question and answer session to ask a question at that time. Please press star one one on your telephone.

Speaker 1: As a reminder, today's call is being recorded. I would like to call on to your house, host Mr. Brian Dignier from ICR. Please go ahead.

Today's call is being recorded.

I turn the call to your house host Mr. Brian <unk> from ICR. Please go ahead.

Great. Thank you Valerie good afternoon, and thank you for joining us today to review Margaret it'd be third quarter of fiscal 2024 financial results, which we announced in our press release issued after close of market today.

Joining me on the call today are David <unk>, President and CEO of Mongo, DB and Michael Gordon Mongo DB C O I went to CFO.

Speaker 2: During this call, we will make four-looking statements, including statements related to our market and the future growth opportunities, the benefits of our product platform, our competitive landscape, customer behaviors, our financial guidance, and our planned investments.

During this call we will make forward looking statements, including statements related to our market and the future growth opportunities.

Benefits of our product platform, our competitive landscape customer behaviors, our financial guidance on our plant and restaurants. These statements are subject to a variety of risks and uncertainties, including the results of operations and financial condition.

Speaker 2: These statements are subject to a variety of risks and uncertainties, including the results of operations and financial conditions, that cause actual results to differ materially from my expectations.

Actual results to differ materially from our expectations.

Speaker 2: For discussion on the material risks and uncertainty is going to affect our actual results, please refer to the risk described in our quarterly report on Form 10Q for the quarter end of July 31st, 2023. That was filed with the SEC on September 1st, 2023.

For a discussion of the material risks and uncertainty as it could affect our actual results. Please refer to the risks described in our quarterly report on Form 10-Q for the quarter ended July 31, 2023 that was filed with the FCC on September one 2023.

Speaker 2: Any forwarding statements made in this call reflect our views only as of today. And we undertake no obligation to up it, um, except as required by law.

Any forward looking statements made on this call reflect our views only as of today and we undertake no obligation to update them, except as required by law.

Speaker 2: Additionally, we will discuss non-GAAP financial measures on this conference call.

Additionally, we will discuss non-GAAP financial measures on this conference call.

Speaker 2: Please refer to the tables in our earnings release on the Investor Relations portion of our website for reconciliation of these measures to their most directly comparable GAAP financial measure. With that, I'd like to...

Please refer to the tables in our earnings release on the Investor Relations portion of our website for a reconciliation of these measures to their most directly comparable GAAP financial measure.

I'd like to turn the call over to Dave.

Speaker 3: Thank you, Brian , and thank you to everyone for joining us today. I'm pleased to report that we had another strong quarter as we continue to execute well despite challenging market conditions.

Thank you, Brian and thank you to everyone for joining us today I'm pleased to report that we had another strong quarter as we continued to execute well despite challenging market conditions I will start by reviewing our third quarter results before giving you a broader company update.

Speaker 3: I will start by reviewing our third quarter results before giving you a broader company up.

Speaker 3: We generated revenue of $433 million, a 30% year-over-year increased, and above the high end of our guide.

We generated revenue of $433 million or 30% year over year increase and above the high end of our guidance Atlas revenue grew 36% year over year, representing 66% of total revenue.

Speaker 3: Atlas revenue grew 36% year-over year representing 66% of total revenue.

Speaker 3: We've generated non-gap operating income by $79 million for an 18% non-gap operating margin. And we had another solid quarter of customer growth ending the quarter with over 46,400 customers. Overall, we delivered...

We generated non-GAAP operating income was 39 million for an 18% non-GAAP operating margin and we had another solid quarter of customer growth ending the quarter with over 46400 customers overall, we delivered a strong Q3.

Speaker 3: We had a healthy quarter of new business acquisition led by continued strength and new workload acquisition when there are existing customers. In addition, our enterprise advanced business, again, exceed our expectations, demonstrating strong demand for our platform and the appeal of our run anywhere, strategy.

A healthy quarter, New business acquisition led by continued strength in new look new workload acquisition within our existing customers. In addition, our enterprise advanced business again exceeded our expectations demonstrating strong demand for our platform and the appeal of our run anywhere strategy.

Speaker 3: Moving on to Atlas Consumption Trends, the quarter played out in line with our expectations. Michael will discuss consumption trends in more detail later.

Moving onto the Atlas consumption trends the quarter played out in line with our expectations, Michael will discuss consumption trends in more detail later.

Speaker 3: Finally, retention rates remain strong in Q3, reinforcing the mission criticality of our platform, even in a difficult spending environment.

Finally retention rates remained strong in Q3, reinforcing the mission criticality of our platform even in a difficult spending environment.

Speaker 3: This quarter we held our most recent global customer advisory board meeting where customers across various jog, freezing industries came together to share feedback and insight about the experience using MongoDB. From these discussions, as well as our ongoing C-suite dialogue with our customers, a few themes emerged.

This quarter, we held our most recent global customer Advisory Board meeting where customers across various geographies and industries came together to share feedback and insight about the experience using <unk>.

From these discussions as well as our ongoing C suite dialog with our customers a few themes emerge.

Speaker 3: First, AI is in nearly every conversation with customers of all sizes. We're seeing great early feedback from our partnership with AWS's CodeWhisperer, the AI-powered coding companion that is now trained on MongoDB data to generate code suggestions based on MongoDB's best practices from over 15 years of history.

First AI is in nearly every conversation with customers of all sizes. We are seeing great early feedback from our partnership with AWS is code whisper. The AI powered cutting companion that is now trained on market data to generate code suggestions based on <unk> best practices from over 15 years of history.

Speaker 3: Microsoft GitHub co-pilot is also proficient at generating code suggestions that reflect best practices, enabling developers to build highly-performing applications even faster on MongoDB.

Microsoft <unk> co pilot is also proficient at generating code suggestions that reflect best practices, enabling developers to build highly performing applications, even faster I'm not going to be.

And with the recent advances in journey II building applications is no longer the sole domain of AI ml experts increasingly it's software developers who are being asked to build powerful functionality directly into their applications. We are well positioned to help them do just that.

Speaker 3: We saw exceptional interest in our vector search public preview and we announced general availability yesterday. Customers are building a range of AI use cases from semantic search to retrieval augmented generation or RAG where organizations can leverage the use of their private data to increase the accuracy of LLM.

We saw exceptional interest in our vectors search public preview and we announced general availability yesterday customers that building a range of AI use cases from semantic search retrieval augmented generation, Iraq, where organizations can leverage the use of their private data to increase the accuracy of LMS for example.

Speaker 3: For example, UKG, a human capital and work flows management technology, stores over 80,000 plus customers around the globe, chose to use MongoDB Atlas vector search for an AI powered assistant that helps guide the customers' employees, people managers and HR leaders.

<unk> of human capital and workflow management technology serves over 80000, plus customers around the globe chose to use <unk> Atlas vector search for an AI powered assistant that helps guide our customers employees people managers and HR leaders.

Speaker 3: They chose Atlas Vector Search because of its minimal added architectural complexity, flexibility to handle rapidly changing data as applications evolve, and the scale to handle large workloads.

They chose Atlas vector search because of its minimal added architectural complexity flexibility to handle rapidly changing data as applications evolve and the scale to handle large workloads.

Speaker 3: UKG is not alone. In a recent state of AI survey report by RITUAL, Atlas Vector Search receives by far the highest net promoter score from developers compared to all other vector databases available in the market.

<unk> is not alone in a recent state of AI Survey report by retail outlets vector search received by far the highest net promoter score from developers compared to all other vector databases available in the market.

Speaker 3: Moreover, developers can combine vector search with any other query capabilities available in MongoDB, namely analytics, tech search, geospatial and time series. This provides powerful ways of defining additional filters on vector-based queries that other solutions just cannot provide.

Moreover, developers can combine vector search with any other query capabilities available in <unk>, namely analytics Tech search Geospatial and time series. This provides powerful ways of defining additional filters on vector based queries that other solutions just cannot provide for.

Speaker 3: For example, you can run complex AI-enriched queries such as find pants, a shirt, shoes in my size that look like the outfit in this image within a particular price range and have free shipping.

For example, you can run complex AI enriched <unk>, such as find pants assured shoes and my size that looked like the outfit in this image within a particular price range and have free shipping.

Speaker 3: or find real estate listings with houses that look like this image that were built in the last five years and are in an area within seven miles west of downtown Chicago with top-rated schools.

Or find real estate listings with houses that looked like this image that were built in the last five years are and are in that area with seven miles west of downtown Chicago with top rated schools.

Speaker 3: Second, customers feel more pressure than ever to modernize their data infrastructure. They are aware that their legacy platforms are holding them back from building modern applications designed for an AI future. However, customers also tell us that they lack the skills and the capacity to modernize. They all want to become modern, but are daunted by the challenges as they're aware it's a complex endeavor that involves technology, process, and people. Consequently, customers are increasingly looking to MongoDB to help them modernize successfully.

Second customers feel more pressure than ever to modernize their data infrastructure. They are aware that there are legacy platforms are holding them back from building modern applications designed for an AI future.

Forever customers also tell us that they lack the skills and the capacity to modernize they all want to become modern but are daunted by the challenges as there where it's complex. It's a complex endeavor that involves technology process and people. Consequently customers are increasingly looking to <unk> to help them modernize successfully.

Speaker 3: We launched relational migrator earlier this year to help customer successfully migrate data from the legacy relational databases to MongoDB. Now we're looking beyond data migrations to the full lifecycle of application modernization.

We launched relational migrate early this year to help customers successfully migrate data from the legacy relational databases to among DB now we're looking beyond data migration for the full lifecycle of application modernization at.

Speaker 3: At our .local London event we unveiled the Query Converter, which uses generative AI to analyze existing SQL queries and stored procedures and convert them to work with MongoDB's Query API.

At our dot local London event, we unveiled the query converter, which uses genetic AI to analyze existing sequel queries and store procedures and convert them to work with <unk> query API.

Speaker 3: Customers already use the tool successfully to convert decades-old procedures to monetize their backend with minimal need for manual changes. While it's still early days, we'll continue to invest in the Query Converter and other AI features with the goal of significantly reducing the effort involved in monetizing legacy applications to run on MongoDB.

Customers already use the tool successfully to convert decades old procedures to modernize their back end with minimal need for manual changes, while it's still early days, we're continue to invest in the query converter and other AI features with the goal of significantly reducing the effort involved and monetizing legacy applications to run on <unk>.

Speaker 3: To be clear, application modernization will take time to ramp, but is one of the largest long-term growth opportunities for our business.

To be clear application modernization will take time to ramp, but as one of the largest long term growth opportunities for our business.

Speaker 3: Third, our Run Anywhere strategy continues to be a real differentiator as customers greatly appreciate the optionality that our platform provides as they manage often conflicting priorities on the way to the cloud.

Third our run anywhere strategy continues to be a real differentiator as customers greatly appreciate the optionality that our platform provides as they manage often conflicting priorities on the way to the cloud on one hand, the movement to the cloud continues unabated customers in industries and geographies, where our first hesitant to move to cloud such as financial service.

Speaker 3: On one hand, the movement to the cloud continues unabated. Customers and industries and geographies who are at first hesitant to move to cloud, such as financial services in Southern Europe , are now moving to the cloud with urgency to become more nimble and to reduce costs.

As in Southern Europe are now moving to the cloud with urgency to become more nimble and to reduce costs. Many of our customers find that the all in costs of maintaining legacy workloads on Prem is higher than the cost of migrating them to the cloud on the other hand, our largest enterprise customers tell us they are planning to maintain a meaningful on prem footprint for the fourth.

Speaker 3: Many of our customers find that the all-in cost of maintaining legacy workloads on-prem is higher than the cost of migrating them to the cloud.

Speaker 3: On the other hand, our largest enterprise customers tell us they are planning to maintain a meaningful on-prem footprint for the foreseeable future. The reasons for keeping workloads on-prem include regulatory requirements

<unk> future the reasons for keeping workloads on Prem include regulatory requirements, the desire to keep using their existing on prem infrastructure or the enormity of the task of migrating all of their apps to cloud in the meantime, they still want a modern data platform to deploy new and existing applications. The continued outperformance of our VA business demonstrates.

Speaker 3: to keep using their existing on-prem infrastructure or the enormity of the task of migrating all their apps to the cloud.

Speaker 3: In the meantime, they still want a modern data platform to deploy new and existing applications. The continued outperforms of EA business demonstrates that our customers value our ability to run anywhere and to future-proof their eventual move to the cloud by building on EA.

That our customers value, our ability to run anywhere and to future proof their eventual move to the cloud by building an EAA.

Speaker 3: Finally, our customers remain focused on cost management. They are looking to do more with less by consolidating vendors and reducing the complexity of the data architecture.

Finally, our customers remain focused on cost management, they're looking to do more with less by consolidating vendors and reducing the complexity of the data architecture.

Speaker 3: MongoDB dramatically increases developer productivity and supports a wide variety of use cases, eliminating the need for many point solutions.

<unk> dramatically increases developer productivity and supports a wide variety of use cases, eliminating the need for many point solutions. This combination resonates with customers in this macro environment.

Speaker 3: This combination resonates with customers in this macro environment.

Speaker 3: For example, Atlas Search now powers the home page of one of the most recognizable sports media brands in the world. The customer replaced an incumbent search technology with Atlas Search because they were drawn to the operational ease of running search queries alongside other queries on Atlas, as well as the overall cost savings from consolidating functionality onto a single platform.

For example, let's search not powers the homepage of one of the most recognizable sports media brands in the world the customer replaced an incumbent <unk> technology with Atlas search because they were drawn to the operational ease of running search queries alongside other queries on Atlas as well as the overall cost savings from consolidating functionality onto a.

Speaker 3: In short, customers view MongoDB as a true partner, a partner that not only accelerates the pace of innovation, but also drives them to become more efficient. We are deepening investments in our product, partnerships, and customer-facing teams to continue to enable customers to do both.

<unk> platform in short customers view <unk> as a true partner a partner that not only accelerates the pace of innovation, but also drives them to become more efficient we're deepening investments in our product partnerships and customer facing teams to continue to enable customers to do both.

Speaker 3: Now I like to spend a few minutes reviewing the adoption trends among to be across our customer base.

Now I'd like to spend a few minutes reviewing the adoption trends among b across our customer base.

Speaker 3: Customers across industries around the world are running mission-critical applications on Atlas, leveraging the full power of our developer data platform. These customers include AT&T, Fishbowl by Glassdoor, and Trend Micro.

Customers across industries around the world are running mission critical applications on Atlas leveraging the full power of our developer data platform. These customers include AT&T fishbowl by Glassdoor and trend micro.

Speaker 3: AT&T's selected Atlas is a key element of their modernization journey. The location-managed application validates 380 million unique customer addresses and handles about 14 million transactions per day. But the various disparate data management solutions led to technical depth and there were duplicative sources of information.

<unk> selected Atlas is a key element of their monetization journey. The location management application validates 380 million unique customer addresses and handles about 14 billion transactions per day, but the various disparate data matching solutions led to technical depth and there were duplicative sources of information the company turned to Atlas as the.

Speaker 3: The company turned to Atlas as a developer data platform to simplify their data infrastructure, merge their data into a single view, and free their teams from managing database operations.

Developer data platform to simplify their data infrastructure merge their data into a single view and free their teams from managing database operations now they rely on Atlas chain streams to easily track changes with data as.

As well as Atlas is native search capabilities and built in geospatial functions to quickly identify location information and accelerate time to market for mission critical products and services.

Speaker 3: EY, Delivery Heel, and ASAP Log are examples of customers turned to MongoDB to free up the developer's time for innovation while achieving significant cost aid.

E Y delivery hero in SaaS log are examples of customers turned to <unk> to free up the developers' time for innovation, while achieving significant cost savings.

Speaker 3: One of the 2023 MongoDB Innovation Award winners is EY. Ernst & Young LLP manages high volumes of transactional data and it's clients and internal teams work on the strict timelines to file taxes and meet regulatory deadlines.

One of the 2023 Mongo DB Innovation award winners as Eli Ernst and young LLP managers high volumes of transactional data and its clients and internal teams work under strict timelines to file taxes and meet regulatory deadlines that cloud based global of that reporting tool or <unk> automates and digitizes the prep.

Speaker 3: The cloud-based Global VAT Reporting Tool, or GVRT, automates and digitizes the preparation of 242 different types of returns across 79 countries.

Creation of 242 different types of returns across 79 countries.

Speaker 3: EY migrated from their previous non-relational database solution to Atlas and experienced a significant performance boost, reduced costs by as much as 50%, and are able to scale without limitations to handle increased data volumes, transaction loads, and concurrent user requests during peak periods.

It migrated from their previous non relational database solution to Atlas and experienced a significant performance boost reduce costs by as much as 50% and are able to scale without limitations to handle increased data volumes transactional loads and concurrent user requests during peak periods.

Speaker 3: EverNorth Health Services, a division of the Cigna Group, Manulife and PlayWalks are turning to MongoDB to modernize applications.

Ever North Health services, a division of the Cigna group Manulife and play walks are turning to <unk> to modernize applications man.

Speaker 3: Manualife, one of the largest life insurance companies in the world, migrates the Atlas when it became clear that their relational database caused a drag on innovation and increased the time to bring new digital products to market.

Your life, one of the largest life insurance companies in the world migrates to the Atlas when it became clear that their relational database cause a drag on innovation and increased the time to bring new digital products to market Manny.

Speaker 3: Manualized selected Atlas because the flexible document model speeds up development, scales easily, supports asset transactions and offers seamless data migration. Using Atlas device syncs, they successfully launch one critical apps offline mode to ensure uninterrupted app usage when offline or in low connectivity areas to improve mobile data synchronization. Using Atlas allows manualized to broaden its digital capabilities and enhance the personalization of customers interactions, cost effect.

Annualized selected Atlas because the flexible document model speeds up development scales easily supports asset transactions and offer seamless data migration using Atlas device Syncs. This successfully launched one critical apps offline mode to ensure uninterrupted app usage when offline or in low connectivity areas to improve mobile.

Data synchronization using Atlas allows many lives to broaden its digital capabilities and enhance the presentation of customers' interactions cost effectively.

Speaker 3: In summary, I'm pleased with the third quarter results, or run any way strategy that has customers' flexibility or where they deploy, and MongoDB is emerging as a platform of choice for their AI-powered applications. And customers are using MongoDB to monitor and become more efficient.

In summary, I am pleased with our third quarter results are run anywhere strategy last customers flexible flexibility over where they deploy and Margaret is emerging as a platform of choice for their AI powered applications and customers are using <unk> to modernize and become more efficient.

Speaker 3: Before I turn it over to Michael, I'm excited to share that Anne Lunis, the former chief marking officer and executive vice president of a corporate strategy in development of Adobe, just joined MangaDB's board of directors.

Before I turn it over to Michael I am excited to share that and Lewis the former Chief marketing Officer, and executive Vice President of corporate strategy and development at Adobe just joined <unk> Board of directors and held leadership roles at Adobe from 2006 to 2023. She was instrumental in driving Adobe has transitioned from a perpetual to subscription base.

Speaker 3: and held leadership role at Adobe from 2006 to 2023. She was instrumental in driving Adobe's transition from her perpetual to a subscription-based business model and has experienced marketing to creative professionals whether they are in a small agency, a medium-sized business or a very large enterprise.

<unk> business model and has experienced marketing to creative professionals, whether they are in a small agency a medium size business are very large enterprise.

Speaker 3: If you replace creative professionals with developers, this strategy is very similar to what MangaDB is doing and entered it at the next level of scale.

You replace creative professionals with developers. This strategy is very similar to what <unk> is doing and ended it at the next level of scale.

Speaker 3: Prior to Adobe and held a variety of leadership positions at Intel during her 20-year tenure at the company, including Vice President of Sales and Marketing, we had thrilled for the exceptional perspective and will bring to the board. With that, here's Mike.

Prior to Adobe and held a variety of leadership positions at Intel during the 20 year tenure at the company, including Vice President of sales and marketing we are thrilled for the exceptional perspective and will bring to the board with that here's Michael.

Speaker 4: Thanks Dave. As mentioned, we delivered a strong performance in the third quarter, both financially and operationally. I'll begin with a detailed review of our third quarter results and then finish with our outlook for the fourth quarter and full fiscal year 2024. First, I'll start with our third quarter results. Total revenue in the quarter was $433 million, up 30% year over year, and above the high end of our guidance. As Dave mentioned, we continue to see a healthy new business environment demonstrating our product market fit and the mission criticality of our plan.

Thanks, Dave as mentioned, we delivered a strong performance in the third quarter, both financially and operationally I'll begin with a detailed review of our third quarter results and then finish with our outlook for the fourth quarter and full fiscal year 2024, first I'll start with the third quarter results total revenue in the quarter was $433 million.

Up 30% year over year and above the high end of our guidance as Dave mentioned, we continue to see a healthy new business environment, demonstrating our product market fit and the mission criticality of our platform sure.

Speaker 4: Shifting to our product mix. Let's start with Atlas. Atlas grew 36% in the quarter compared to the previous year and represents 66% of total revenue compared to 63% in the third quarter of fiscal 2023 and 63% last year.

Shifting to our product mix, let's start with Atlas.

Atlas grew 36% in the quarter compared to the previous year and represents 66% of total revenue compared to 63% in the third quarter of fiscal 2023, and 63% last quarter.

Speaker 4: As a reminder, we recognize Atlas revenue primarily based on customer consumption of our platform and that consumption is closely related to end user activity of the application, which can be impacted by macroeconomic facts.

As a reminder, we recognize Atlas revenue, primarily based on customer consumption of our platform and that consumption is closely related to end user activity of the application, which can be impacted by macroeconomic factors.

Speaker 4: Let me provide some context on Atlas consumption in the quarter. Week over week consumption growth in Q3 was in line with our expectations and stronger than Q2. As a reminder, we were expecting a seasonal uptick in consumption in Q3 compared to Q2 based on what we had experienced and shared with you last year. We had forecast that seasonal improvement to be less pronounced this year compared to last year, given that overall we've seen less consumption variability this year and that is exactly how the quarter played out.

Let me provide some context on Atlas consumption in the quarter week over week consumption growth in Q3 was in line with our expectations and a stronger than Q2 as a reminder, we were expecting a seasonal uptick in consumption in Q3 compared to Q2 based on what we've experienced and shared with you last year, we had forecast that that seasonal improvement to be.

Less pronounced this year compared to last year given.

Given that overall, we've seen less consumption variability this year and then exactly how the quarter played out.

Speaker 4: Turning to non-atlas revenues. EA exceeded our expectations in the quarter as we continue to have success selling incremental workloads into our existing EA cup.

Turning to non Atlas revenues exceeded our expectations in the quarter as we continue to have success selling incremental workloads into our existing EAA customer base ongoing strength speaks to the appeal and the success of our run anywhere strategy. The AA revenue outperformance was in part a result of more multiyear deals than we had expected.

Speaker 4: ongoing EA Strength speaks to the appeal and the success of our run anywhere strategy. The EA Revenue Out performance was in part a result of more multi-year deals than we had expected. As a reminder, the term license component for multi-year deals is recognized as upfront revenue at the start of the contract and therefore includes term license revenues from future years.

As a reminder, the term license component for multiyear deals as recognized as upfront revenue at the start of the contract and therefore includes term license revenues from future years.

Turning to customer growth.

Speaker 4: During the third quarter we grew our customer base by approximately 1,400 customers sequentially bringing our total customer count to over 46,400, which is up from over 39,100 in a year ago period. Of our total customer count over 6,900 direct sales cuts.

During the third quarter, we grew our customer base by approximately 1400 customers sequentially, bringing our total customer count to over 46400, which is up from over 39100 in the year ago period of our total customer count over 6900 are direct sales customers, which compares to over 5900 in the year ago period.

Speaker 4: which compares to over 5,900 in the year-to-year-go period. The growth in our total customer count is being driven primarily by ATLAS, which had over 44,900 customers at the end of the quarter compared to over 37,600 customers in the year-to-year-go period. It is important to keep in mind that the growth in our ATLAS customer count reflects new customers among UDB in addition to existing EA customers adding incremental ATLAS workloads.

The growth in our total customer count is being driven primarily by Atlas, which had over 44900 customers at the end of the quarter compared to over 37600 customers in the year ago period. It is important to keep in mind that the growth in our Atlas customer count reflects new customers demand going to be in addition to existing EA customers, adding.

It'll Atlas workloads.

Speaker 4: During the quarter, we moved approximately 350 accounts representing negligible ARR out of our self-serve customer count because they're better classified as substitute areas of other customers, or they're now users of our free tier. Taking that into account, our self-serve net additions and overall net additions remain consistent with our historic healthy trip.

During the quarter, we moved approximately 350 accounts, representing negligible IRR out of our self serve customer count because they are better classified as subsidiaries of other customers, where they are now users of our free tier.

That into account our self serve net additions and overall net additions remain consistent with our historic healthy trends in terms of our direct sales net additions new sales activity remains healthy our reported direct sales net adds continue to reflect the dynamics, we discussed last quarter related to leveraging cloud provider marketplaces to fulfill new direct sales customer.

Speaker 4: In terms of our direct sales net additions, new sales activity remains healthy. Our reported direct sales net ads continue to reflect the dynamics we discussed last quarter related to leveraging cloud provider marketplaces to fulfill new direct sales customer additions, and the movement of some small mid-market direct sales counts to self-serve. Moving on.

Additions and the movement of some small and mid market direct sales accounts to self serve.

Moving on to <unk>.

Speaker 4: We had another quarter with our NetAR expansion rate above 120%. We ended the quarter with $1,972 customers with at least $100,000 in ARR and annualized MRR, which is up from $1,545 in the year ago period. Moving down the income statement, I'll be discussing our results on a non-gap basis and let's otherwise note it.

Had another quarter with our net expansion rate above 120%. We ended the quarter with 1972 customers with at least $100000 in <unk> and annualized MRI, which is up from 1545 in the year ago period.

Moving down the income statement I'll be discussing our results on a non-GAAP basis, unless otherwise noted.

Speaker 4: Gross profit in the third quarter was $335.3 million, representing a gross margin of 77%, which is up from 74% in the year ago period. Our year-over-year margin improvement is primarily driven by improved efficiencies that we are realizing in-app.

Gross profit in the third quarter was $335 3 million, representing a gross margin of 77%, which is up from 74% in the year ago period, our year over year margin improvement is primarily driven by improved efficiencies that we are realizing in apps.

Speaker 4: Our income from operations was $78.5 million or an 18% operating margin for the third quarter. Compared to a 6% margin in the year ago period, our strong bottom line results demonstrate the significant operating leverage in our model and our clear indication of the strengths that are underlying unit economics.

Our income from operations was $78 5 million or an 18% operating margin for the third quarter compared to a 6% margin in the year ago period, our strong bottom line results demonstrate the significant operating leverage in our model and are a clear indication of the strength in our underlying unit economics. The primary reason for our operating income results versus guidance.

Speaker 4: The primary reason for our operating income results versus guidance is our revenue output.

Speaker 4: In addition, our operating income benefited from the timing of new hires. Finally, Q3 benefited from the timing of marketing programs, internal events, and other expenses, which we now expect to occur in Q4.

As our revenue outperformance. In addition, our operating income benefited from the timing of new hires finally, Q3 benefited from the timing of marketing programs internal events and other expenses, which we now expect to occur.

Incur in Q4.

Speaker 4: Net income in the third quarter was $79.1 million or 96 cents per share based on 82.7 million diluted weighted average shares outstanding. This compares to a net income of 18.7 million dollars or 23 cents per share on 80.4 million diluted weighted average shares outstanding in the year ago period.

Net income in the third quarter was $79 1 million or <unk> 96 per share based on $82 7 million diluted weighted average shares outstanding. This compares to a net income of $18 7 million or 23 per share on $80 4 million diluted weighted average shares outstanding in the year ago period.

Speaker 4: Turning to the balance sheet and cash flow, we ended the third quarter with $1.9 billion in cash, cash equivalents, short-term investments, and restricted cash. Operating cash flow in the third quarter was $38.4 million. After taking into consideration approximately $3.5 million in capital expenditures and principal repayments of finance lease liabilities, free cash flow was $35 million in the quarter. This compares the negative free cash flow's $8.4 million in the third quarter of fiscal 2023.

Turning to the balance sheet and cash flow. We ended the third quarter with $1 $9 billion in cash cash equivalents short term investments and restricted cash operating cash flow in the third quarter was $38 4 million after taking into consideration approximately $3 5 million in capital expenditures and principal repayments are final.

<unk> <unk> lease liabilities free cash flow was $35 million in the quarter. This compares to negative free cash flows $8 4 million in the third quarter of fiscal 2023.

Speaker 4: I'd now like to turn to our outlook for the fourth quarter and full year fiscal year 2020

I would now like to turn to our outlook for the fourth quarter and full year fiscal year 2024.

Speaker 4: For the fourth quarter, we expect revenue to be in the range of $429,000,000 to $433,000,000. We expect non-gap income from operations to be in the range of $35,000,000 to $38,000,000,000, and non-gap net income per share to be in the range of $0.44 to $0.46,000, based on 83.2 million estimated looted weighted average shares up to 10.

For the fourth quarter, we expect revenue to be in the range of $429 million of $433 million. We expect non-GAAP income from operations to be in the range of $35 million, a $38 million and non-GAAP net income per share to be in the range of 44 to 46.

Based on $83 2 million estimated diluted weighted average shares outstanding.

Speaker 4: For the full year fiscal 2024, we are increasing our outlook across the board.

For the full year fiscal 2024, we are increasing our outlook across the board. We now expect revenue to be in the range of $1 654 billion to $1 65 8 billion non.

Speaker 4: We now expect revenue to be in the range of $1.654 billion to $1.658 billion.

Speaker 4: Non-Gap income from operations to be in the range of $236.3 million to $239.3 million and non-Gap net income per share to be in the range of $2.89 to $2.91 based on 82.5 million estimated diluted weighted average shares out.

non-GAAP income from operations to be in the range of $236 3 million to $239 3 million and non-GAAP net income per share to be in the range of $2 89 to.

To $2 91.

Based on $82 5 million estimated diluted weighted average shares outstanding note that the non-GAAP net income per share guidance for the fourth quarter and full fiscal year 2024 includes a non-GAAP tax provision of approximately 20%.

Speaker 4: Note that the non-gap net income per share guidance for the fourth quarter and full fiscal year 2024 includes a non-gap tax provision of approximately 20%.

Speaker 4: I'll now provide some context on our guidance. First, we expect Q4 atlas consumption growth to be impacted by the seasonal slowdown around the holidays.

I'll now provide some context on our guidance first we expect Q4 Atlas consumption growth to be impacted by the seasonal slowdown around the holidays.

Speaker 4: Second, as you think about both sequential and year-over-year revenue growth of Atlas and Q4, keep in mind that in Q4 last year, we had several million dollars more of revenue coming from unused commitments, which we do not expect to occur this quarter.

Second as you think about both sequential and year over year revenue growth of Atlas in Q4 keep in mind that in Q4 last year, we had several million dollars more of revenue coming from unused commitments, which we do not expect to occur this quarter.

Speaker 4: Third, as a result of our strong execution so far this year, we are again raising our non-atlas revenue expectations for Q4.

Third as a result of our strong execution. So far this year, we are again, raising our non Atlas revenue expectations for Q4.

Speaker 4: However, we expect that our non-atlus revenues will decline sequentially Q4 versus Q3. This is different from our normal pattern as we usually see a seasonal upkicking Q4 due to greater renewal activity. The reason for the sequential decline this year is because of the strength we've seen in Q3, including the benefit of multi-year EADL.

However, we expect that our non Atlas revenues will decline sequentially Q4 versus Q3. This is different from our normal pattern as we usually see a seasonal uptick in Q4 due to greater renewal activity. The reason for the sequential decline. This year is because of the strength, we've seen in Q3, including the benefit of multi year deals.

Speaker 4: Finally, thanks to the strong performance in Q3 and the increased revenue outlook, again, we are again increasing our assumption for operating margins in fiscal 24 to 14% at the midpoint of our guidance, and improvement of more than 900 basis points compared to fiscal 23.

Finally, thanks to the strong performance in Q3 and the increased revenue outlook again, we are we are again, increasing our assumption for operating margins in fiscal 'twenty, 4% to 14% at the midpoint of our guidance an improvement of more than 900 basis points compared to fiscal 'twenty three.

Speaker 4: Our significant margin improvement this year is primarily driven by our revenue outperformance and the fact that we didn't increase our pace of investment as the revenue outlook improved until relatively late in the year. As a result, we achieved greater margin expansion this year than we think is desirable in the short term given the long-term market opportunity ahead of.

Our significant margin improvement. This year is primarily driven by our revenue outperformance and the fact that we didn't increase our pace of investment is the revenue outlook improved until relatively late in the year. As a result, we achieved greater margin expansion. This year that we think is desirable in the short term given the long term market opportunity ahead of us to <unk>.

Speaker 4: To summarize, MongoDB delivered excellent third quarter results in a difficult environment. We're pleased with our ability to win new business and are demonstrating the operating leverage inherent in our model. While we'll continue to monitor the macro environment, we remain incredibly excited about the opportunity ahead, and we'll continue to invest responsibly to maximize our long-term value. With that, we'd like to open up to questions. Operator.

<unk> I'm going to be delivered excellent third quarter results in a difficult environment. We're pleased with our ability to win new business and are demonstrating the operating leverage inherent in our model. While we will continue to monitor the macro environment. We remain incredibly excited about the opportunity ahead, and we will continue to invest responsibly to maximize our long term value.

With that we'd like to open up to questions operator.

Speaker 1: Thank you. Again, ladies and gentlemen, if you'd like to ask a question, please press star 11 on your telephone. Again, to ask a question, please press star 11. We do ask if you please limit yourself to one question on the follow up, one moment for our first question.

Thank you again, ladies and gentlemen, if you like to ask a question. Please press star one on your telephone again to ask a question. Please press star one win we do ask that you. Please limit yourself to one question and a follow up one moment for our first question.

Speaker 1: Thank you. Our first question comes from Sanjit Singh, a Morgan Stanley , a lot of...

Thank you. Our first question comes from sang Jin sang of Morgan Stanley. Your line is open.

Speaker 5: Thank you for taking the questions and congrats on the results in Q3. We'll look at the atlas growth this quarter. Michael, I know you mentioned that

Thank you for taking the questions and congrats congrats on the results in Q3.

When you look at the Atlas growth this quarter, Michael I know you mentioned that.

Speaker 5: that the consumption trends were better than expectations. In terms of the seasonality that you were anticipating and that what I've shown up in the business in the past two years, was that more pronounced than you expected? Or did that come in below in terms of the seasonal up list that you've seen in Q.

That the consumption trends were.

Better than expectations in terms of the seasonality that you were anticipating as well.

I showed up in the business in the past two years was that more pronounced than you expected or did that come in below in terms of the the seasonal uplift that you've seen in Q3.

Speaker 4: Yeah, so just to clarify, Q3 for Atlas came in line with our expectations. We had seen and called out last year seasonal seasonality for Q3. We had expected that and incorporated that into our forecast. What we have seen is less variability over the course of the year. And so we assume that that Q3 seasonality would be more muted this year. And that's exactly what happened in how the quarter played.

Yes, so just to clarify Q3 for Atlas came in line with our expectations, we had seen and called out last year.

Isn't all seasonality for Q3.

We had expected that and incorporated that into our forecast what we have seen is less variability over the course of the year and so we.

Assume that that Q3 seasonality would be more muted this year and thats exactly what happened and how the quarter played out.

Speaker 5: Oh, understood. Thank you Michael for the clarification. And then Dave, I guess a much bigger picture question, you know,

Well understood. Thank you. Thank you Michael for the clarification, and then Dave I guess, a much bigger picture question.

I think the company was founded in 2007, so its about 17 years into the journey and if you compare that to some of the large incumbent players.

Speaker 5: And if you compare that to some of the large income to the players in the space like an Oracle, around this time, 17 to 20 years in, they started to move away from the data management, database space.

Players in the space like an Oracle.

Around this time, you know seven team to kind of 20 years and they started to move away from like the data management database space.

Speaker 5: and intellect the application software market. Is that a vision, particularly in the dawn of this sort of...

And then to like the application software.

Market is that a vision, particularly as one of the dawn of the sort of new compute cycle with AI is that an analogy that applies to mongo.

Speaker 5: cycle with AI. Is that an analogy that applies to Mongo in terms of its long-term roadmap in your view?

In terms of its long term roadmap.

Speaker 3: Yeah, thanks for your question, Sondip. What I would say is, we've been very clear that we're really pushing our developer data platform.

Yes.

Yes, Thanks for your question.

What I would say is we've been very clear that we are really pushing our developer data platform.

Speaker 3: strategy and we think the market is way larger today than it was for Oracle when they were essentially 17 years old and our developer that data platform strategy is really very simply enabling

Strategy and we think the market is way larger today than it was for Oracle and they were essentially 17 years old and our develop our data platform strategy is really very simply enabling developers to use modeling to be for a wide variety of use cases across a wide variety of deployment models whether.

Speaker 3: developers use MongoDB for a wide variety of use cases across a wide variety of deployment models, whether it's on-prem, on the cloud, multi-cloud, or even at the edge.

It's on Prem or on the cloud multi cloud or even at the edge and so thats really our strategy.

Speaker 3: And so that's really our strategy. We don't see any need to get into, quote unquote, the application space itself. And we think that we have a lot of runway ahead of us. I appreciate it, son. Stay safe. Thank you.

Don't see any need to get into quote unquote the application space itself.

And we think that we have a lot of runway ahead of us.

I appreciate it thank you.

Thanks Sandeep.

Thank you one moment please.

Okay.

Speaker 1: Our next question comes in the line of Ramos Lensgal of Barclays, Atlanta.

Our next question comes from the line of Raimo <unk> of Barclays. Your line is open.

Speaker 6: Thank you. Congrad for me as well. I wanted to ask on EA first, another very strong quarter there. Can you talk a little bit more on the driver's gear? Because I do seem to remember you kind of doubled down on sales capacity. I think it was junior sales guy that you wanted to put on existing accounts. Is that kind of a main driver? Or is it more modernization?

Thank you.

For me as well.

I wanted to ask on E <unk>.

Another very strong quarter. There can you talk a little bit more on the drivers Gary because I do seem to remember you kind of double down on seal capacity I think it was junior acetyl Scott that you wanted to put on existing accounts is that kind of a main driver or is it more like modernization.

Speaker 6: are kind of picking up a lot more than what we thought would be possible. Can you speak to that? Because it's like the second quarter in a row where we kind of have better numbers there. And then I have one follow up for a minute.

Kind of picking up a lot more than what we thought would be possible can you speak to that.

The second quarter on a rolling wherever you kind of a better number Sam and I have one follow up for Michael.

Speaker 3: As a RIMO, with regards to our EA outperformance, I think it really speaks to a run anywhere strategy where customers really value the ability to build on MongoDB and for essentially future proof their deployment model, whether they stay on-prem.

Yeah, So raimo with regards to our outperformance.

Performance I think it really speaks to our run anywhere strategy, where customers really value the ability to build on <unk> essentially is future proof their deployment model, whether they stay on Prem also move to the cloud or move from one cloud to another cloud and the fact that it can do that without having to rewrite the application is very compelling for customers.

Speaker 3: Also, you move to the cloud or move from one cloud to another cloud. And the fact that it can do that without having to rewrite the application is very compelling for customers.

As you also said a lot of customers still especially the largest customer still have a lot of sunk cost and they want to leverage their existing data infrastructure. So a lot of customers have told us that they will still deploy.

Infrastructure on Prem for the foreseeable future, but what I building on market be they get the benefits of a modern platform and the Optionality to also move the cloud when they are ready to do so.

Speaker 4: Yeah, the other thing which I know, you know, Rymel, but just for the broader audience, you know, we run the business on a channel basis. Sales isn't oriented around, you know, products. And then also, as we've said before, EA tends to be the additional sales of EA tend to be to existing customers. We don't tend to land a ton of new, brand new customers on EA.

Yes, the other thing, which I know you know raimo, but just for the broader audience. We run the business on a channel basis sales isn't oriented around products.

And then also as we've said before EBITDA tends to be the.

Additional sales of EAA tend to be two existing customers, we don't tend to land a ton of new brand new customers.

Speaker 6: Okay, perfect. And then the follow up is more, it's around AI. So if I look at the demos that you guys have around vector search and how search is getting a lot better, that seems very compelling and it seems like really straightforward for a client to improve their customer experience if they use it for a customer-facing up, for example. What is the implications for growth margins for you, Michael? Like, do you have to do a lot more compute here to be able to handle it? How should we think about that in terms of extra revenue? But then also extra cost coming through. Thank you.

Okay, Perfect and then follow up is more it's around AI.

If I look at the demos that you guys have their own vector search and how search is getting a lot better that seems very compelling and it seems like really straightforward for a client to improve there.

Customer experience they use it for a customer facing App for example, what is the what.

What are the implications for gross margins for you Michael like do you have to do a lot more compute there to be able to handle it how should we think about that in terms of extra revenue, but then also extra costs coming through thank you.

Speaker 4: Yeah, so I think it's a little too early to tell is obviously plenty of variability, you know, in the workloads, you know, depending on the nature, you know, of what the underlying, you know, application is. So I think it's a little early to give a strong, you know, direction to that. I think more broadly on margins, we've certainly been very happy with the margin progress that we've made. I referenced the, you know, continued efficiencies that we're driving in Atlas. You know, Atlas is roughly two thirds of the business. So is that continues?

Yes, so I think it's a little too early to tell there's obviously plenty of variability in the workloads.

Depending on the nature.

What the underlying application and so I think it's a little early to give a strong.

<unk> to that I think more broadly on margins, we've certainly been very happy with the margin.

Yes that we've made I referenced the continued efficiencies that we're driving in Atlas Atlas is roughly two thirds of the business. So as that continues.

Speaker 4: to increase, you know, at least still is lower margin, you know, overall. And so that will have some impact, you know, you know, over the next several years, but we were really pleased on the margin front, but I think too early to make a specific...

To increase outlet still is lower margin overall, and so that will have some impact.

Over the next several years, but we're really pleased on the on the margin front, but I think too early to make a specific call or quantification on the gross margin impacts of AI.

Speaker 3: call or quantification on the growth margin is the impact of AI. Yeah, and Rhyme, just to add to that, one of the announcements we also made was that you can now do workload isolation for search or vector search functionality. You can scale those notes independently of your overall cluster.

And Brian just to add to that one of the announcements. We also made was that where you can now do workload isolation. So for search of Vectra search functionality you can scale those nodes independently of the overall cluster. So what that really does is allow customers to really configure their clusters to have the right level of performance at the most efficient cost so we've been very sensitive.

Speaker 3: So what that really does is allow customers to really configure their clusters to have the right level performance at the most efficient.

Speaker 3: So we've been very sensitive on making sure that based on the different use cases, you can scale up and down different nose based on...

Making sure that based on the different use cases, you can scale up and down different knows based on your application needs are by definition that would be a very compelling value proposition for customers.

Speaker 7: Your application needs, by definition, that will be a very compelling valley proposition for customers. Okay, perfect. Thank you.

Perfect. Thank you.

Thank you one moment please.

Speaker 1: Our next question comes from a line of Carl Kierstedt, of UBS, and I-

Our next question comes from the line of Karl Keirstead from UBS. Your line is open.

Speaker 8: Great, thanks. Maybe I'll direct this question to Dave. I think a lot of people on the line are hearing this refrain about.

Great. Thanks, maybe I'll direct this question to Dave Dave I think a lot of people on the line are hearing this refrain about customers enterprises wanting to get their data as states and order in advance of moving forward on AI initiatives and you even spoke about customers feeling pressure to modernize their data infrastructure.

Speaker 8: customers enterprises wanting to quote get their data estate in order in advance of moving forward on AI initiatives and you even spoke about

Speaker 8: customer ceiling pressure to modernize their data infrastructure. I just like to ask where we are in that journey. Is this a conversation that your sales teams are having? Or do you feel like this is actually beginning to...

Sure.

Like to ask where we are in that journey as this.

Is this a conversation that your sales teams are having or do you feel like this is actually beginning to result in deals and revenue pull through and if it isn't yet roughly when do you think that might start to translate to an actual revenue lift.

Speaker 8: result in deals and revenue pull through and if it isn't yet roughly when do you think that might start to translate to an actual revenue list

Speaker 3: Yeah, so I'll make a couple of points. Carl, you're absolutely right. There's a lot of focus on data because with AI, data in some way becomes a new code. You can train your models with your proprietary data that allows you to really drive much more value and build smarter applications. Now, the key thing is that it's operational data because with applications,

Yes, so I'll make a couple of points Carl Youre, absolutely right. There is a lot of focus on data because with AI data in some ways becomes a new code you can train your models with your proprietary data that allows you to really drive much more value and build smart applications now the key thing is.

Is that its operational data because with applications. This data is always costly being updated and for many customers. Most of those applications are right now running on legacy platforms. So that operational data is trapped in those legacy platforms and you can't really do a batch process of E. Tailing all that data into some sort of warehouse and then still be able.

Speaker 3: And you can't really do a batch process of e-telling all that data into some sort of warehouse and then still be able to leverage the real time use of that data. That's why customers are now much more interested in potentially modernizing these legacy platforms than they ever have before. I would say, Carl, to your second part of your question, I would say it's still very, very early days. We definitely believe that this will be one of the largest long-term opportunities for our business.

To leverage the real time use of that data. That's why customers are now much more interested in potentially modernizing these legacy platforms than they ever have before I would say call. It to your second part of your question I would say, it's still very very early days, we definitely believe that this will be one of the largest long term opportunities for our business.

Speaker 3: but uh... you know we're in the very early days and and i've said that the past there's a risk of overestimating the impact the short term but underestimate the impact of long term we definitely think this along

But we're in the very early days and as I've said in the past there is a risk of overestimating the impact in the short term, but underestimated the impact of long term. We definitely think this is a long term impact okay, great and if I could ask a follow up to Mike on a different subject. Mike you had talked on the last call a little bit more about this mix shift away from multi.

Speaker 8: Okay, great. And if I could ask a follow up to Mike on a different subject.

Speaker 8: Mike, you had talked on the last call a little bit more about this mixed shift away from multi-year atlas commit and you were pointing to that as a reason for some of your metrics like DR and I think even cash flow to come under a little pressure. This quarter I see DR is still under pressure. Cash flow was a little bit better. Can you maybe revisit that phenomenon and describe how it's impacting some of these metrics?

Year Atlas commit and you were pointing to that as a reason for some of your metrics like Dr and I think even cash flow to come under a little pressure. This quarter I see Dr is still under pressure cash flow was a little bit better can can you maybe revisit that phenomenon and describe how it's impacting some of these metrics.

Speaker 4: Yeah, a couple of things as we've said from the beginning, some of those like calculated billings or deferred revenue metrics, you know, aren't super helpful or don't provide a ton of insight in terms of how we.

<unk>.

Yes, a couple of things as we've said from the beginning some of those like calculated.

Billings or deferred revenue metrics arent super helpful or don't provide a ton of insight in terms of how we run the business. We've also talked about.

Speaker 4: run the business. We've also talked about how, over the last couple years, one of the things we've been trying to do is reduce friction for the sales force. Some of that includes reducing the emphasis around upfront

How over the last couple of years, one of the things <unk> been trying to do is reduce friction for the sales force some of that includes reducing the emphasis around upfront commitments.

Speaker 4: And so that helps accelerate landing new workloads and things like that. And that will flow through or does flow through. The financial statements, as less up front deferred and things like that. And so it allows us to sort of synthetically cover more ground from a Salesforce perspective. And so you do see that continuing to go through. We shared this that.

So that helps accelerate landing, new workloads and things like that and that will flow through where it does flow through the.

The financial statements as less upfront deferred and things like that.

And so but allows us to sort of.

Synthetically covered more ground from a salesforce perspective until you do see that continuing to go through we shared this at the <unk>.

Speaker 4: The statistic last quarter, that the Atlas revenue growth last quarter was 38%, but dollars of committed Atlas declined 15% year of a year, just as one way to try and help dimensionize it. We also talked, I think earlier in the year, about how roughly 80% of Atlas...

<unk> last quarter.

The Atlas revenue growth last quarter was 38%, but dollars of committed Atlas declined 15% year over year, just as one way to try and help dimensionalize. It. We also talked I think earlier in the year about how roughly 80% of Atlas doesn't flow through deferred and so I think all of those data points help kind of lineup to explain the rest of what you're seeing and why.

Speaker 4: doesn't flow through deferreds. And so I think all of those data points help kind of line up to explain the rest of what you're seeing and why that's not sort of a helpful forward-looking metric like it might be in other companies. It doesn't kind of give you the insight that maybe people are used to or hope that that will provide. Yep, that's clear. Thanks a lot. Thanks, Carl.

That's not sort of a hopeful forward looking metric like it might be in.

In other companies it doesn't kind of give you the insight that maybe people are used to our hope that that will provide.

That's clear thanks a lot.

Thanks Carl.

Thank you one moment please.

Speaker 1: Our next question comes in a lot of Brad Rebick of Steve Fuljolana.

Our next question comes from the line of Brad <unk> of Stifel. Your line is open.

Speaker 9: Great, thanks very much. Michael, maybe following up on that last question in your commentary. At what point should DR...

Great. Thanks, very much Michael maybe following up on that last question and your commentary at what point should Dr.

Speaker 9: stopping a headwind from a financial perspective. One should it stabilize, or is this a multi-year trend as you kind of bleed it down?

Stop being a headwind.

From a financial.

Perspective, one should it stabilized.

Or is this a multiyear trend.

As you kind of bleed it down.

Speaker 4: Yeah, so I'd say there are a couple things. Obviously, it's not something we guide to. It's not a key thing that we focus on, but I think the trends will be, you've got sort of two factors. One is overall atlas mix, right? And so to the extent that atlas continues to grow, that will provide a headwind on the dynamic. And then similarly, even within the current.

Yes, so I'd say there are a couple of things obviously, it's not something that we guide to it's not a key thing that we focus on but I think the trends will be you've got sort of two factors. One is overall atlas mix right and so to the extent that Atlas continues to grow that will provide a headwind on this dynamic and then similarly.

Even within the current Atlas footprint.

Speaker 4: Atlas footprint. There's this historic commitments that we need to run through renewal cycles and everything else. And so I think this will take a little while still to play out.

There is this historic commitments that we need to run through renewal cycles, and everything else and so I think this will take a little while still to play out.

Speaker 9: Great. And then switching gears, Dave, as customers began to trial, excuse me, some of these co-pilot A code tools will say, what type of feedback have you gotten from them as it relates to the pace with which they've been able to reduce net new workload time to market? How much faster or efficient art customers getting using these tools?

Great and then switching gears, Dave as customers begin to trial.

Excuse me.

Some of these co pilot.

Code tools will say.

What type of feedback have you gotten from them as it relates to that.

With which they've been able to reduce.

Net new workload.

To market, how much faster or efficient our customers getting using these tools.

Yes.

Speaker 3: We get different answers from a lot of different customers. It really depends on which tool they're using. Without commenting on who's better, who's worse, we definitely see a difference in the quality of the output between the different tools. I think it's gonna take some time.

<unk>.

We get different answers from different customers, it really depends on which tool they are using.

Without commenting on who's better whose worst we definitely see a difference in the quality of the output, which is a different tools I think it could take some time for these tools to mature so I think youre seeing a lot of customers do a lot of testing and prototyping.

Speaker 7: for these tools to mature. So I think you're seeing a lot of customers do a lot of testing and prototyping. I would also tell you that they're doing a lot of this on internal facing applications because there's still lots of questions about IP rights and what is potentially copyrightable and then also be licensed if they offer this as a...

I would also tell you that they're doing a lot of this on internal facing applications, because there's still lots of questions about IP rights and what is potentially copyrightable then ultimately licensed bowl if they offer this as a.

Speaker 7: shrink-wrap software or service to their end customers. So we're seeing more of this work on internally facing applications, but the productivity gains really do vary by tool, and also vary by the sophistication of the app being built. So it's hard for me to give you a real number. I know there's people out there quoting 30 or 40% improvements, but it really depends on the customer and the use case and the tool that they're trying to use. So it'd be hard for me to give you a specific number. Thanks very much. Thank you.

Shrink wrap software service to their end customers. So we're seeing more of this work on internally facing applications, but the productivity gains really do vary by tool and also very do vary by the sophistication of the App being built so it's hard for me to give you a real number I know there's people.

Out there, it's floating 30 year, 40% improvements, but it really depends on the customer and the use case and the tool that they are trying to use so it would be hard for me to give you a specific number.

Okay. Thanks very much thank.

Thank you thank you Brad.

One moment please.

Speaker 1: Our next question comes from a lot of Palo Radkib City, a lot of...

Our next question comes from a lot of Tolerability of Citi. Your line is open.

Speaker 9: Yeah, thanks for thinking the question. So earlier this quarter, you hired Mark Porter's replacement, Jim Sharf from AWS, who is a lot of experience in the database industry. Can you just talk about some of his priorities, what you're kind of accelerating in terms of the product roadmap to sell to larger enterprises?

Yes, thanks for taking the question.

Earlier this quarter you hired.

Mark quarters replacement, Jim sharp from from AWS.

A lot of experience in the database industry can you just talk about.

Some of his priorities, what youre kind of accelerating in terms of the product roadmap.

To sell to.

Speaker 3: Yeah, so for those people who don't know Jim's background, he spent about 17 years at AWS. He had a variety of roles. But last to, you know, many for roles was he ran the Dynamo business at AWS, which is AWS's.

Larger enterprises.

Yes, so for those people, who don't know Jim's background, you spend about 17 years at AWS you have had a variety of roles.

The last two meaningful roles was he ran the Dynamo business at AWS, which is AWS is faster.

Speaker 3: fastest growing and largest non-relational database business. And then you ultimately then took over that identity access, management business, which if you think about it, every AWS customer has to use. So it's a service that has to not only perform, but perform at massive scale, but the fact that you've dealt and built two mission critical services for AWS.

<unk> fastest growing and largest non relational database business and then ultimately then took over that identity access management business, which if you think about it every AWS customers to use so it's a service that has to not only perform but perform at massive scale. The fact Tv's Dell and built two mission critical services for AWS.

Speaker 3: was very appealing to us, given our ambitions to kind of, and the level of skill that we expect our business to get to at some point in time. He obviously, you know, brings us very strong technical DNA. He obviously has a lot of network of relationships in the industry, so we expect him to help us grow the team around the world, leveraging his relationships.

<unk> was very appealing to us given our ambitions to kind of level of scale that we expect our business ultimately to get to at some point in time.

C <unk>.

Brings us very strong technical DNA.

Obviously, there's a lot of network of relationships in the industry. So we expect them to help us grow the team.

Around the world.

Speaker 3: And in terms of priorities, I mean right now he's still kind of really assessing the current state of the business. He's been quite impressed with the quality of the town that we have. But he's really kind of what I'd, you know, what I'd encourage him to do was, you know, we need to go slow to go fast to take his time in terms of really understanding the business, understanding the team, understanding the code base before he starts really prioritizing what to do. And it's not like this one, things massively broken. It's really helping us set up to scale to the next level.

<unk> has relationships and in terms of priorities I mean right now he is still kind of really assessing the current state of the business. He has been quite impressed with the quality of town that we have but he is really kind of what I would encourage them to do is we need to go slow to go fast to take his time in terms of really understanding the business understanding the team understanding.

The code base before he starts really prioritizing what to do and it's not like this on things massively broken it's really helping us set up to scale to the next level.

Speaker 9: Great. And a follow-up for Michael, I know you, you talked about how Atlas consumption during Q3 was in line with your expectations. I'm just curious, given there were a lot of volatility in at least the equity markets and the economy, did it, was there any more, you know, variability within the quarter? You know, in other words, did it start weaker and stronger? And then I'm just curious.

Great.

Michael I know you talked about how Atlas consumption. During Q3 was in line with your expectations.

Sure.

I'm just curious given there were a lot of volatility in at least the equity markets and the economy did it did was there anymore.

Variability within the quarter in other words did it start weaker and stronger and then I'm just curious throughout the month of November.

Speaker 5: throughout the month of November , you know, if things kind of further improved ahead of the holiday season now, they just any additional color would be helpful. Thank you.

Have things kind of further improved ahead of the holiday seasonality.

Any additional color would be helpful. Thank you.

Speaker 4: Yeah, so it last said Q3 Atlas results were in line with our expectations. There was a seasonal benefit to Q3 relative to Q2, but given that fact that we've seen less variability and consumption in fiscal 24, we had expected that to be smaller than it was in fiscal 23, and that's exactly how it played out.

Yes.

So unless you said Q3 Atlas results were in line with our expectations there was.

Seasonal benefit to Q3 relative to Q2.

But given the fact that we've seen less variability in consumption in fiscal 'twenty. Four we had expected that to be smaller than it was in fiscal 'twenty three and that's exactly how it played out.

Speaker 4: The seasonal improvement as it relates to Q3 is a little bit more in the back half of the quarter. As it relates to Q4, typically the back half is weaker, given the holiday slowdown. And so hopefully that helps people understand a little bit.

The seasonal improvement.

As it relates to Q3 is a little bit more.

In the back half of the quarter.

As it relates to Q4 typically the back half is weaker given the holiday slowdown and so hopefully that helps people understand a little bit.

Thank you one moment please.

Speaker 1: Our next question comes from the line of cash ringing, of Goldman fractional.

Our next question comes from the line of Kash Rangan of.

Goldman Sachs. Your line is open.

Speaker 10: Hey, thank you very much, David Michael. Happy holidays, congrats on those else. So going into calendar 24, how does the management team feel relative to going into calendar 23, with respect to how macro conditions are no longer impacting or maybe they are impacting?

Hey, Thank you very much David Michael It's happy holidays, and congrats on good results.

So going into calendar 'twenty four.

Feel relative to going into calendar 'twenty, two with respect to how macro.

Patients are no longer impacting or maybe they are backing.

Speaker 10: some aspects of the business, any verticals that stand out that you feel particularly excited about. So just wanted to understand how MongoDB is therefore fitting into customer priority as you get into 24. Thank you so much.

Some aspects of the business.

Any verticals that stand out that you're particularly excited about.

So just wanted to understand.

<unk> is therefore fitting into customer priority and as you get into going forward. Thank you so much.

Speaker 3: Hey, Cash. Thanks for the question. I think compared from last year, this year we don't see things getting worse, but we don't see things getting better.

Hey, Kash.

Thanks for the question.

Think compared from last year. This year, we don't see things getting worse, but we don't see things getting better.

Speaker 3: uh... where i said last year with the fed raising rates you could really then that people are getting much more cautious

What I said last year with the fed raising rates you can really sense that people are getting much more cautious and and it was.

Speaker 3: And it was probably more negativity in terms of the outlook coming into calendar 2023. So that being said, we definitely see innovation being a priority for customers. We clearly are, I would say, in the distinction between must have and nice to have it clearly in the first category.

Probably more negativity in terms of the outlook coming into calendar 2023.

So that being said.

We definitely see innovation being a priority for our customers.

Clearly our I would say the distinction between must have a nice to have or clearly in the first category.

Speaker 3: But customers are also, as I mentioned, the prepared remarks remain focused on being sensitive to costs and ensuring that any investments that make have a high ROI. So we feel that we're well positioned in terms of use cases or segments. I would say in general, there's no real kind of material change in any across any...

But customers are also as I mentioned in the prepared remarks, we remain focused on <unk>.

Being sensitive to cost and ensuring that any investments that may have a high ROI. So we feel that we're well positioned.

In terms of use cases, our segments I would say in general.

There's no real kind of material changes across any vertical industry or geography, we do see I mean, we're at re invent last week and we had an amazing set of conversations with lots of senior level customers.

Speaker 3: vertical industry, a geography, we do see, and we were at re-invent last week, and we had an amazing set of conversations with lots of senior level customers. I think we're really viewed as a mission-critical platform by all our customers, and I think people view us as a platform that can bet on long-term. And so we see less, I would say, focused on point solutions and more about trying to leverage MongoDB for more and more use cases.

I think we're really viewed as a mission critical platform by by all our customers and I think people view us as a platform that they can bet on long term and so we see less I would say focus on like point solutions and more about like trying to leverage marketing for more and more use cases.

Speaker 3: And I would say that's pretty consistent across industry and jobs.

And I would say that that's pretty consistent across.

Industries and geographies, yes, the only other thing I'd add cash is clearly things have stabilized.

Speaker 7: Yeah, the only thing I'd add, Tash, is clearly things have stabilized. We are not guiding fiscal 25, but just looking out there's clearly a difficult EA and non-EA compare that people should sort of keep in mind. And I think the big assumption or the big determiner will be people's macro outlook in terms of how that affects the fiscal 25 numbers. But those are probably the key things to keep in mind.

We are not guiding fiscal 'twenty five.

But just looking out there is clearly a difficult.

At non EEA compare.

That people should keep in mind, and I think the big assumption or the big determinant will be people's macro outlook in terms of how that affects the fiscal 'twenty five numbers.

But those are probably the key things to keep in mind.

Thank you one moment please.

Sure.

Our next question comes from the line of <unk> Kidron.

Speaker 11: I've been having a lot of f-

Of Oppenheimer. Your line is open.

Speaker 9: Thanks, guys. Nice numbers. Michael, I want to go back to one of the comments in the prepared remarks. I think you've talked about how you expect non-athletes business to be down quarter to quarter to quarter.

Okay.

Hey, guys nice numbers.

Michael I want to go back to one of the comments in your prepared remarks, I think you've talked about how you expect non atlas business to be down quarter over quarter in the fourth quarter.

Speaker 9: because I think the third quarter had multiple multi-year deals. Correct me if I've got this wrong. I guess my question is why would that affect for Q on list? It was a pull forward also, not just multi-years. Easier a pull forward element from four Q into three Q in your non-athletes business.

Because.

I think the third quarter had multiple multiyear deals are correct me if I forgot this wrong.

I guess my question is why would that effect for Q unless there was a pull forward also and not just multi years is there a pull forward element from <unk> into <unk> and your non <unk> business.

Speaker 4: No, it's not about a pull forward. It's just when you take into account the 6-0-6 impact of a multi-year deal, you wind up recognizing a lot of upfront license revenue. And so when you think about what that means on a sequential basis, you see the difference of the delta there.

It's not about a pull forward. It's just when you take into account the 606 impact of a multiyear deal you wind up recognizing a lot of upfront license revenue and so when you think about what that means on a sequential basis you see the difference of the Delta there got it helpful. And then therefore you Andre.

Speaker 4: God it's helpful. And then therefore you want to... I think the only thing ETI just for people is, given the strength that we've seen of EA throughout the year, but including Q3, we effectively raised our outlook, if you will, in Q4, in part given the strength of EA. Even though we don't guide to product, you can, you know, Atlas was in line with our expectations.

I think the only other thing <unk> just for people is given.

Given the strength that we've seen throughout the year, but including Q3, we effectively raised our outlook if you will.

In Q4 in part given the strength of EAA, even though we don't guide to product you can Atlas was in line with our expectations outperformed.

Speaker 4: EA outperformed in Q3 and our full year, you know, raise was more than.

Outperformed in Q3.

And our full year raise was more than the beat in Q3, and I think that shows the continued strength of any yet.

Speaker 4: the BQ3 and I think that shows the kind of continued strength of any

Speaker 9: Got it, helpful. And then Dev, on vector search, I know this is kind of fresh out of the oven here, but maybe you can talk about the opportunity here on a per customer basis. How do I think about the dollar potential here? And is there one common vendor out there that you expect to see more in competition for those types of use cases?

Got it helpful and then Dave on <unk>.

The search I know this is kind of a fresh out of the oven here, but maybe you can talk about the opportunity here on a per customer basis, how do we think about the dialog dollar potential here and he is there one common vendor out there that you expect to see more.

In competition for those types of use cases.

Speaker 3: Yeah, so let me start with the second question first. I would say that I think, you know, six, six, nine months ago, there was a lot of interest in vector databases, and there were some point solutions that got a lot of name recognition, and a lot of people wondering, is there a risk, you know, that we could be destructed by them? And at that point in time, we made it clear that we believe vectors.

Yes, So let me start with the second question first I would say that I think six to nine months ago. There was a lot of interest in Vectra databases and there are some point solutions that got a lot of name recognition than a lot of people are wondering is there a risk that we could be disrupted by them and at that point in time. He made it clear that we believe vectors.

Speaker 3: We're really another form of an index and that every database platform would also incorporate vectors into their architecture. And the winner really would be the technology that made the vector functionality very integrated and cohesive as part of the developer workflow. I would argue that that's really played out as I said in the prepared remarks. That was a recent.

We're really another form of an index and that every database platform would ultimately incorporate vectors into their architecture and the window really would be the.

The technology that made the vector functionality very integrated and cohesive as part of the developer workflow.

I would argue that has really played out as I've said in the prepared remarks, there was a recent.

Speaker 3: Analysis done by a Consolency firm called retool that really spoke to lots of customers and we came out of top on In terms of NPS and by the way our product was a preview product. It wasn't even the GA product We've seen a lot of demand from customers and And we feel like this is a big big opportunity Again early days You know it's gonna take time to materialize, but this is again one of the other big growth opportunities for our business

Analysis done by Consol.

Consultancy firm called retool that really spoke to lots of customers and we came out on top in terms of NPS and by the way our product was a preview product it wasn't even the GAA product, we've seen a lot of demand from customers and.

And we feel like this is a big big opportunity.

Again, it's early days.

It's going to take time to materialize, but this is again one of the other big growth opportunities for our business that being said in terms of the revenue opportunity is really hard to quantify now because of use cases that customers are starting with are still kind of I would say early in <unk>.

Speaker 3: That being said, in terms of the revenue opportunity, it's really hard to quantify now because the use cases that customers are starting with are still kind of, I would say early in the day of the day of the day, because people are still playing around with the technology. But we are seeing, as I mentioned, you know, UKG is using it to essentially provide a AI-powered assistance.

Because people are still playing around with the technology.

But we are seeing.

As I mentioned U K G is using it to essentially.

Speaker 3: for its people You know one energy European energy company is using

AI powered assistant.

For its people.

One energy European Energy company is using.

Speaker 3: has terabytes of geospatial data and is using vectors to basically get better insights in terms of the images that they're getting from the work they're doing in terms of drilling for oil. So it's still very, very early days. It's a hard to give you like exact numbers. Even today, even in our general non-AI workloads, the workload variety can vary a lot depending on the customer, the number of users, the amount of data. So I think it's going to be similar to our core business, which is that just...

As terabytes of geospatial data and is using.

Vectors to basically get better insights in terms of the images that theyre getting from from.

The work, they're doing in terms of drilling for oil. So it's still very very early days. So hard to give you like an exact numbers even today, even in our general non AI workloads. The workload variety can vary a lot depending on the customer the number of users the amount of data. So I think it's going to be similar to our core business, which is that it just really depends on the use case.

Speaker 12: Appreciate it. Thank you.

Alright I appreciate it thank you.

Yes.

Thank you one moment please.

Speaker 1: Our next question comes from a line of Brad Phil's Bank of America. A line of...

Our next question comes from the line of Brad Sills with Bank of America. Your line is open.

Speaker 4: Oh, great, thanks so much. One of the ask a question around the customer count greater than 100K, it looks like a real nice result this quarter. Is there any change going on there in terms of the trajectory or the path for customers to get to that level? In other words, are they starting bigger, are they landing bigger, or are they just getting to that point faster? So, the question is, is there any change going on there in terms of the trajectory or the path for customers to get to that level?

Oh, great. Thanks, so much.

I wanted to ask a question around the customer count greater than 100, K. It looks like a real nice result, this quarter.

Is there any change going on there in terms of the trajectory or the path for customers to get to that level. In other words are they starting bigger are they landing bigger.

Or are they just getting to that point faster and what would be driving those two things.

Speaker 3: Yes, I'm glad you called that out, Brad. Yeah, I think we added 117, 100K customers this quarter, which is the largest ad I think in the company's history. What I think it really speaks to is that customers are increasingly viewing MongoDB as a mission critical platform. They're gonna run more and more workloads on MongoDB. So by definition, it's rare that one workload on its own will drive that kind of revenue. So at the multiple workloads,

Yes.

I'm glad you called that out Brad yes.

I think we added 117.

<unk> customers this quarter, which is the largest AD I think in the company's history.

I think it really speaks to is that customers are increasingly viewing mom going to be as a mission critical platform, they're going to run more and more workloads among IDB so by definition.

It's rare that one workload on its own will drive that kind of revenue.

Speaker 3: And really, jeering us as a standard part of their infrastructure stack is what's really drawing that number and we're obviously happy to see the results of that. And we think that that's just indication, as I said earlier, where people are consolidating onto a few vendors, they recognize that we offer a support for broad set of use cases. We're truly a general purpose, which is a critical platform, and that their developers really love using mommy.

Multiple workloads.

And really getting us as a standard part of their infrastructure stack is what's really driving that number and we're obviously happy to see the results of that and we think that that's just indication as I said earlier, where people are consolidating onto a few vendors.

They recognize that we offer.

For a broad set of use cases, we are truly a general purpose mission critical platform and that their developers really loved using Margaret.

Speaker 4: And then one more if I may please, I'm the commentary around, you know, customers viewing mango is that platform with some of these newer workloads besides search like relational migrator, you know, add the

Wonderful to hear and then one more if I may please.

The commentary around customers viewing bango is that platform with some of these newer workloads besides search like relational migrate or.

Speaker 13: Are you finding that that receptivity for customers who want to run, you know, search within, you know, one single solution? Is that also the case for streaming and relational? Just trying to get a sense for, you know, those cycles and how those might ramp up.

Atlas streaming do you are you finding that that receptivity for customers, who want to run search within one single solution is that also the case for streaming in relation I was just trying to get a sense for those cycles and how those might ramp on that platform capability. Thank you.

Speaker 3: Yeah, so actually, yeah, one of the reasons we actually built search is because we got feedback from our customers. In many instances, a lot of our customers were dual-homing data, two MongoDB and two some sort of search database. So consequently, not only had to manage two databases, keep that data in sync, but also manage the plumbing that connected those two database platforms.

Yes so.

Actually one of the reasons, we actually built searches because we got feedback from our customers in many instances lottery customers were dual homing data to model it to be and to some sort of search database. So consequently, not only had to manage two databases keep that data and saying, but also manage the plumbing that connected those two database platforms and customers told us.

Speaker 3: And customers told us they much would say like, we don't understand why you're not offering a solution because we much rather.

Much like we don't understand why you are not offering a solution because we much rather.

Speaker 3: you know have it all in one platform with one API and that ultimately drove our desire to build out our search functionality which is

Have it all in one platform with one API.

And that ultimately drove our desire to build out our search functionality, which is really becoming more and more popular. So the point for customers is that if you can remove friction in terms of how they can use the platform.

Speaker 3: It really becoming more and more popular. So the point for customers is that if you can remove friction in terms of how they can use the platform, leverage the platform, have one set of kind of semantics in terms of to address a broad set of use cases, it really simplifies the data architecture and the more you simplify data architecture, the more nimble you can be and the more cost effective you can be. And I think that's what's really resting with customers.

Leverage the platform have one set of kind of semantics in terms of to address a broad set of use cases, it really simplifies the data architecture and the more you simplify data architecture. The more nimble you can be in a more cost effective you can be and I think that's what's really resonating with customers.

Thank you so much Dave.

Thank you one moment please.

Speaker 1: Our next question comes from a line of Rishi, Celuria.

Our next question comes from the line of Richie Deloria.

Of RBC your line is open.

Speaker 14: Oh, wonderful. Thanks so much for taking my question. Maybe I want to start by diving a little bit into relational migrator. David, I know you said it, definitely early days, but where you are seeing usage of it, maybe can you give us a little bit of color? What sort of workloads are these that customers are utilizing the tool for? What does that timeline look like? And, in color, you can give there in terms of early adoption would be really helpful. And I've got a quick follow.

Wonderful. Thanks, so much for taking my question.

Maybe I want to start by diving, a little bit into relational migrate or Dave I know you said, it's definitely early days, but where you are seeing usage of it maybe can you give us a little bit of color what sort of workloads are the that customers are utilizing the tool for what is kind of that timeline look like any color you can give there in terms of early adopters.

The option would be really helpful. And then I've got a quick follow up.

Speaker 3: Yeah, so again, as you can imagine, given the, you know, a lot of these legacy platforms that are around for between 30 to 40 years, a lot of people have a large repository of legacy apps.

Yes so.

Again.

As you can imagine given.

Lot of these legacy platforms that are around for between 30% to 40 years a lot of people have a large repository of legacy apps.

Speaker 3: And migrating off a legacy platform to another platform does require some work. It requires essentially three things. One, you have to map the schema of the old platform onto the new platform. You then have to move the data. And then you have to rewrite the application code.

And.

Migrating off a legacy platform to.

Another platform does require work it requires.

Essentially three things one you have to map the schema of the old platform onto the new platform. You would then have to map move the data and then you have to rewrite the application code and those three things took some time. So we heard feedback when we when we took the company public you might remember that 30.

Speaker 3: And those three things took some time. So we heard feedback. When we took the company public, you might remember that 30% of our net new business at the time went public was actually relational migration. So customers were undertaking that heavy lifting because they were in such pain and wanted to move to a more modern platform.

2% of our net new business at the time when public was actually a relational microbes migration. So customers were undertaking that heavy lifting because they were in such pain and wanted to move to a more modern platform, but clearly.

Speaker 3: But clearly, that pain can basically be a bit of a tax on switching costs. And so essentially, we build tooling based on feedback from customers to start automating the schema mapping and the data movement.

That pain can can basically be a bit.

Bit of a tax on switching cost and so essentially rebuild tooling based on feedback from customers to start automating. The scheme are mapping in the data movement now with the availability of Gen. AI. You can also now start automating the cogeneration associated with rebuilding or rebuilding and application and.

Speaker 3: Now with the availability of Gen AI, you can also now start automating the co-generation associated with rebuilding or rebuilding an application. And essentially what, rather than thinking about just

Essentially what rather than thinking about just.

Speaker 3: You know, moving at the app, you know, in one lock step, we can actually break down a monolithic relational app into microservices and start cleaving off different parts of the services first.

Moving into the App.

One lock step, we can actually breakdown of monolithic relational app into micro services and start cleaving off different parts of the services first so it can be a much more efficient and also more ROI quicker ROI on some of the investments we're making so there is a big big opportunity here for us to do that but again I want to be very clear we view this as.

Speaker 3: So it can be much more efficient and also a quicker ROI and some of the investments are making.

Speaker 3: So there's a big, big opportunity here for us to do that. But again, I want to be very clear. You know, we view this as...

Speaker 3: long-term growth opportunity. We're still in the very early days. We've got some really interested customers who are doing some interesting things and working with us on pilots.

Long term growth opportunity, we're still in the very early days <unk> got some really interested customers who are doing some interesting things in working with us on pilots.

Speaker 3: Our engineering and product and field teams are really focused on this, but we're in the very, very early days of really automating, you know, relational migrator to the next level leveraging.

Our engineering and product and field teams are really focused on this but we are in the very very early days of really automating.

<unk> migrated to the next level leveraging <unk> AI.

Speaker 14: All right, wonderful. That's really helpful. But then I wanted to ask about MongoDB serverless. I know this is something you've kind of had, at least been talking about for a while.

Alright wonderful Thats really helpful. And then I wanted to ask about Mongo DB server less I know this is something you've kind of had.

He has been talking about for a while given a lot of the concerns around cloud optimization or rationalization customers overpaying and having to figure out how to optimize our footprint.

Speaker 14: Given a lot of the concerns around cloud optimization and rationalization, and customers overpaying and having to figure out how to optimize their footprint.

Speaker 14: It feels like that could be a natural tailwind for MongoDB serverless, especially because you were early to embrace it. Can you talk a little bit about what you're seeing in terms of adoption there, how we should be thinking about that opportunity, and maybe just kind of what this could look like over the next several years in terms of...

Looks like that could be a natural tailwind for Margo DB, several especially because you were early to embrace it can you talk a little bit about what youre, what youre seeing in terms of adoption there how we should be thinking about that opportunity and maybe just kind of what this could look like over the next several years in terms of service adoption.

Speaker 14: serverless adoption versus traditional consumption adoption in Atlas. Thanks.

Versus traditional consumption adoption and Atlas.

Speaker 3: Yeah, so just to be clear, when we talk about serverless, basically what customers think about is that they don't have to start thinking about capacity planning.

Yes, so just to be clear when we talk about surplus basically but.

What customers think about is that they don't have to start thinking about capacity planning that the workload can scale up and scale down based on the needs of whatever the use cases in and what the compute and and other resource needs are and so.

Speaker 3: that the workload can scale up and scale down based on the needs of whatever the use case is and what the compute and other resource needs are. And so.

Speaker 3: So there's been a lot of interest from customers. At first age it was a lot of ephemeral workloads where they didn't want to go provision a dedicated cluster. They wanted to be able to leverage our serverless functionality. We think long term that almost every workload will become serverless because over time that'll be the...

So there's been a lot of interest from.

From customers.

At first stage was lot of ephemeral workloads, where they didn't want to go provision of dedicated cluster. They wanted to be able to leverage our service functionality. We think long term that almost every workload will become <unk> because over time that will be the the way most applications are provisioned, but we're in the early days and the receptivity in use.

Speaker 3: the way most applications are provisioned, but we're in the early days and the receptivity and use of our service functionality has been very high. And you're right, it's...

Of our service service functionality has been very high and you are right.

Speaker 3: for those legacy platforms that they can't offer similar solutions.

For those legacy platforms or they can't offer a similar solutions marketing me becomes that much more attractive because a development team and architecture team doesn't have to worry about capacity planning. They can just build the app and they know in the background.

Speaker 7: our infrastructure can scale up and down as their usage, you know, as their usage goes up and down.

Our infrastructure can scale up and down as their usage.

As the usage goes up and down.

Alright wonderful very helpful. Thank you.

Thank you one moment please.

Speaker 1: Our next question comes from the line of Brett Braceland of Piper Family. Your line is open.

Our next question comes from the line of Brent break Lynn Piper Sandler Your line is open.

Brent price Lynn Youre line is open.

Speaker 15: Oh, hi, guys. This is Hannah on for Brent. Thanks for taking my question. Just one for me. Subscription gross margins remained above 80% for the second straight quarter, even with that continued makeshift to Atlas. I know you mentioned efficiency improvement to Atlas, but are we at a structural point, Michael, where the scale of gross margins can remain at that 80% plus range into the next year?

Oh, Hi, guys. This is Hannah on for Brian. Thanks for taking my question just one from me.

Subscription gross margins remained above 80% for the second straight quarter, even with that continued mix shift to Atlas I know you mentioned efficiency improvement to Atlas, but are we at a structural point, Michael where the scale.

Gross margin can remain at that 80% plus range into the next year.

Speaker 4: Yeah, so what I would say is I do not think I think if you think about it, Atlas gross margins continue to be lower than enterprise advanced gross margins. And while we're very pleased with the 80% margin performance.

Yes so.

I would say is I do not think I think if you think about it Atlas gross margins continue to be lower than enterprise advanced gross margins and while we're very pleased with that 80% margin performance.

Speaker 3: you know, on a subscription margin basis in Q3, Atlas is, quote unquote, only two-thirds. And so, you know, there is still a delta between the two. And so, you know, I think that that will have a slightly dilutive effect on margins as Atlas increases as a percent of overall revenue. Okay. It makes sense.

On our subscription margin basis in Q3 Atlas is quote unquote only two thirds and so there is still a delta between the two and so I.

I think that that will have a slightly dilutive effect on margins as Atlas increases as a percent of overall revenue.

Okay makes sense. Thank you.

Thank you one moment please.

Speaker 1: Our next question comes from the line of Patrick Colville of Scotiabank, your line is open.

Our next question comes from the line of Patrick Colville of Scotiabank. Your line is open.

Speaker 16: Hi, this is Joe Vandrick on for Patrick Colville. As of 3Q, it looks like about 29% of direct sales customers are spending over 100K on the platform. Just curious where you think that percentage can trend over the longer term and how big the opportunity is within these existing direct sales.

Hi, This is Joe <unk> on for Patrick Colville.

As of <unk>, it looks like about 29% of direct sales customers are spending over 100 K on the platform. Just curious where you think that percentage can trend over the longer term and kind of how big the opportunity is within these existing direct sales customer accounts. Thanks.

Yeah, Joe I would say that we still believe that we have a very small percentage of wallet share in most accounts and so obviously the smaller customer.

Bigger the wallet share, but in most direct sales customers our percent of wallet share is still quite small so we see a big opportunity there and as we talked about in terms of our new business a big part of our new business came from acquiring new workloads with existing customers and that is a big focus for our go to market teams and.

Speaker 3: And the runway is quite long for that trend.

And the runway is.

Long for that trend to continue.

Great and just one more for me.

I mean, you've kind of touched on this but whats the feedback then from from this customers have used vector search.

And preview.

And then obviously with.

With vector search comes quite a bit more data so.

How are you, making sure that customers don't receive.

A surprise bill and up.

Speaker 3: Yeah, so as we mentioned earlier, the feedback on our vector search has been very high. Even when it was in public preview, we were getting a lot of feedback.

Unhappy.

Yes so.

As we mentioned earlier the feedback on our vectors search has been very high even when it was in public preview we were getting a lot of feedback and then we saw this report that came out obviously, we don't talk to.

Speaker 3: And then we saw this report that came out, obviously we don't talk to, you know, customers, people who are using alternatives, we just talk folks on our own customers.

People, who are using alternatives just to talk folks on our own customers, but.

Speaker 3: But it was, you know, we're pleased to see that out of all the products available in the marketplace, our own preview product had the highest NPS score. So then if you unpack that, why do customers like using MongoDB? Because it's one tightly integrated solution. You can tightly integrate capturing vector data, metadata, and then data regarding, you know, the particular use case. And that becomes very, very attractive. It just becomes much more seamless and easier to use versus either using point solutions or some Clujie.

We're pleased to see that out of all of the products available in the marketplace our own previous product had the highest NPS score. So then if you unpack that why do customers like use among DB because as one tightly integrated solution you can tightly integrate capturing vector data metadata and then data regarding.

The particular use case and that becomes a very very attractive. It just becomes a much more seamless and easier to use versus either using point solutions or some clue G.

Speaker 7: you know, a solution that's been put together. So I think that's a big reason about how we remove friction from a developer's workflow and why, you know, the MongoDB approach makes it so much better to, you know, to use than say any other alternative approach.

Solution, that's been put together so I think that's a big reason about how we remove friction from a developer's workflow and why the marketing approach makes it so much better to use it to any other alternative approach in terms of your question around.

Speaker 3: In terms of your question around the amount of data and the data bills, obviously, vectors can be memory intensive.

The amount of data and data builds obviously vectors can be memory intensive and.

Speaker 3: And the amount of vectors you generate will obviously drive the amount of usage on those nodes. That's one of the reasons we also introduced dedicated search nodes. So you can asymmetrically scale particular nodes of your application, especially your search nodes, without having to increase the overall size of your cluster. So you're not-

The amount of vectors you generate will obviously drive the amount of usage on those knows that's one of the reasons. We also introduce dedicated search knows so you can asymmetrically scale particular nodes of your application, especially your search nodes without having to increase the overall size of your cluster. So you are not.

Speaker 3: you know, after your point, talk to the big bill for underlying usage, for non-usage, right? So, you only scale the nodes that are really need that incremental compute and memory versus nodes that don't, and that becomes a much more cost-effective way for people to do this. And obviously that's another differentiator from MongoDB.

To your point soft with a big bill for underlying usage for non usage right. So so you're only scaled nodes that are really need that incremental compute and memory versus note that don't and that becomes a much more cost effective way for people to do this and obviously that's another differentiator for <unk>.

Got it thank you.

Thank you.

Speaker 1: That is all the time that we have today for today's conference. I'm just trying to call back over to Deb Itchichira, CEO for any closing remarks.

That is all the time that we have today for today's conference I'd like to turn the call back over to Deb <unk> CEO for any closing remarks.

Speaker 3: Thank you. I appreciate everyone joining the call today. Again, I just want to reiterate that we had another strong quarter of new business performance validating the value proposition of our developer data platform and our run anywhere strategy. We are seeing strong momentum on AI strategy, especially Atlas Vector Search, which is emerging as a best-of-class solution for building powerful AI applications. And we continue to help customers drive greater efficiency while also accelerating their pace of innovation.

Thank you.

I appreciate everyone joining the call today again I just wanted to reiterate that we had another strong quarter new business performance validating the value proposition of our developer data platform and our run anywhere strategy.

We're seeing strong momentum on our AI strategy, especially Atlas Vectra search, which is emerging as a best in class solution for building powerful AI applications and we continue to help customers drive greater efficiency, while also accelerating their pace of innovation, so with that I.

Speaker 3: So with that, I appreciate your time and it will talk to you soon. Take care.

I appreciate your time and we'll talk to you soon take care.

Speaker 1: Thank you. Ladies and gentlemen, this is the SESC Inclusive Conference. Thank you all for participating. You may now disconnect.

Ladies and gentlemen, this does conclude today's conference. Thank you all participating you may now disconnect.

Okay.

Okay.

Okay.