Q1 2024 MongoDB Inc Earnings Call

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Thank you for standing by and welcome to MongoDB's first quarter, fiscal year 2024 earnings conference call. At this time, all participants are in a listen only mode. After the speaker presentation, there will be a question and answer session. To ask a question during the session, you will need to press star, one, one.

which we announced in our press release issued after the closing market today.

Jordan, me and the call today are Dave Ida Charia, President and CEO of MongoDB, and Michael Gordon, MongoDB, COL and CFO .

including statements related to our market and future growth opportunities, the benefits of our product platform, our competitive landscape, customer behaviors, our financial guidance, and our planned investments.

These statements are subject to a variety of risks and uncertainties, including the results of operations and financial conditions, because actual results differ materially from our expectations.

For discussion of the mature residence third to consider the effect of actual results, please refer to the risk described in our annual report on Form 10K for the year ended January 31, 2023, followed with the SEC on March 17, 2023.

take no obligation to update them except as required by law.

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

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

tables and earnings release on the investor relations portion of our website for a reconciliation of these measures to their most directly comparable GAAP financial measures. With that, I'd like to turn the call over to Dave.

Thanks, Brian . And thank you to everyone for joining us today. I'm pleased to report that we had another strong performance of the first quarter, and we continue to execute well despite challenging market conditions. I will start by reviewing our first quarter results before giving you a broader company update. But first, I would like to personally invite all of you to the investor session at my...

increase and above the high end of our guidance. Atlas Revenue grew 40% year of year representing 65% of revenue and we had another strong quarter of customer growth, any of the quarter with over 43,100 customers.

Overall, we delivered a strong Q1. We had a very healthy quarter of new business acquisition. We added approximately 2,300 customers during the quarter, the highest number in over two years, including over 300 new direct sales customers, with notable strength in our enterprise channel. Our ongoing new business success is due to the mission criticality of our platform.

Moving on to Atlas consumption trends, Q1 consumption was ahead of our expectations, but remains below the levels we saw prior to the macro slowdown that began last year. Michael will share more detail on this.

Finally, retention rates remain strong in Q1, reinforcing the enduring value in our platform. We are pleased with our results this quarter, especially given the difficult macro environment. It's clear customers continue to scrutinize their technology investments and must decide which technologies our must have versus a merely a nice to have.

We believe there are Q1 performance and continuing new business strength demonstrate that MongoDB is clearly a must-have for customers. In today's digital economy, most companies express their business strategy through software. They use software to deliver their core value proposition, provide customers with great experiences and drive operational efficiency.

MongoDB is an essential platform in this dry for innovation, making us a critical investment priority.

Our customers ranging from the largest companies in the world to cutting-edge startups, user developer data platform to develop and run mission-critical applications.

As your applications become successful, customers spend more with MongoDB. In other words, their spend on our platform is directly aligned with their usage of their underlying application. Therefore, the value they derive from it.

While the growth rate of existing applications can vary based on a number of factors, including macro conditions, the relationship between application usage and growth, application usage growth, and MongoDB spend has remained consistent.

We believe this is a testament to how well our value proposition is aligned to our customer's success.

Thinking about a long-term opportunity, I feel exceptionally confident about our core underlying growth driver, the need for companies to use software as a competitive advantage. Customers have ever increasing expectations for better products, services, and experiences, and companies rely on custom-built software to deliver these expectations better and faster than their competition.

As I said many times have passed, a durable competitive advantage is built through custom software. It cannot be obtained with an off-the-shelf product.

Since most companies understand that day in their competition are all differentiating themselves through software, the speed of software development becomes existential. A McKinsey report found that companies that score in the top quartile of developer velocity generate revenue growth that is four to five times faster than companies in the bottom quartile.

MongoDB is built for speed.

increase in software development velocity. We know that most organizations have a huge backlog of projects they would like to take on, but they just don't have the development capacity to pursue. As developer productivity meaningfully improves, companies can dramatically increase their software ambitions and rapidly launch many more applications to transform their business.

Consequently, the importance of development velocity to remain competitive will be even more pronounced. Set another way, if you are slow, then you are obsolete.

Moral with a shift to AI will favor modern platforms that offer a rich and sophisticated set of capabilities, delivered in a performant and scalable way.

We are observing an emerging trend where customers are increasingly choosing outlets at the platform to build and run new AI applications.

For example, in Q1, more than 200 of the new Outlet customers were AI or ML companies.

Well, finance startups like HuggingFace, Tekian, OneAI, and Neuro are examples of companies using MongoDB to help deliver the next wave of AI-powered applications to their customers. We also believe that many existing applications will be a platform to be AI-enabled. This will be a compelling reason for customers to migrate from legacy technologies to MongoDB.

To summarize, AI is just the latest example of a technology that promises to accelerate the production of more applications and greater demand for operational data stores, especially the ones best suited for modern data requirements, such as MongoDB.

We look forward to telling you more at our Investor session on June 22nd.

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

MongoDB's developer data platform continues to gain momentum as customers across industries and around the world are running their mission critical projects on Atlas. Organizations including anywhere real estate, GE Healthcare, and into it are leveraging the power of our developer data platform. GE Healthcare has turned to MongoDB's developer data platform to manage

health care providers enhanced productivity by reducing the complexity and time required to manage databases, resulting in an 83% decrease in data retrieval time and enabling faster deployment of IoT devices.

Many customers are turning to MongoDB to free up the developer's time for innovation, enabling them to move faster and deliver better customer experiences while driving cost savings. This includes China Mobile, Tata Digital, and Grand Thorton International.

China Mobile provides mobile voice and multimedia services via its nationwide mobile telecom network across mainland China and Hong Kong. It is the world's largest mobile network operator by total number of subscribers.

The Telecom Leader is using MongoDB to support one of the largest and most critical push services, which sends out billing details to more than 1 billion users every month.

Prior to MongoDB, the tech team relied on Oracle, but as the user numbers increased, performance degraded.

Despite large investments, it was still taking too long to do basic requests like finalize and deliver build to users.

As a result, China Mobile migrated the service to MongoDB after comprehensive testing and evaluation of alternatives. By taking advantage of MongoDB's native sharding, they are able to improve performance by 80% and go from 50 Oracle machines to just 12 machines for the same workload. The service now handles all current requirements.

and set up to scale with Future Growth.

Digital transformation is redefining how organizations operate, and MongoDB is helping customers on this journey by delivering the developer data platform that powers their migration from on-premises to the cloud. Companies including Shutterfly, Radial, Bendigo, and Adelaide Bank are an example of customers leveraging MongoDB in their transformations.

our job finding tech space shifted from MongoDB community to MongoDB Atlas during this journey to migrate its entire infrastructure from on-premises to the cloud. They selected MongoDB Atlas to give its developers full autonomy over their data, while freeing up the time they previously spent managing their database system to focus on innovation and improving the end user experience.

During the migration during the Atlas, the company identified opportunities for significant infrastructure reduction and subsequent cost savings. In addition, the company has experienced 250% faster query performance and 300% faster write throughput on their application's built on Atlas. In summary, I am pleased with our first quarter results in a difficult macro environment.

Our ability to win new workloads remains strong, and Atlas consumption trends were better than expected. We also believe that AI will accelerate application development, which would further stimulate demand for MongoDB. We continue to invest to maximize our long-term growth opportunity. With that, here's Michael.

Thanks Dave. As mentioned, we delivered a strong performance in the first quarter, both financially and operationally.

I'll begin with the detailed review of our first quarter results, and then finish with our outlook for the second quarter and full fiscal year 2024.

detailed review of our first quarter results, and then finish with our outlook for the second quarter and full fiscal year 2024. First, I'll start with our first quarter results.

Total revenue in the quarter was $368.3 million, up 29% year over year. As Dave mentioned, we continue to see a healthy new business environment, both in terms of acquiring new customers as well as acquiring new workloads within existing customers.

To us, this is confirmation we remain a top priority for our customers and our value proposition continues to resonate even in this market.

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

Atlas grew 40% in the quarter compared to the previous year and represents 65% of total revenue compared to 60% in the first quarter of fiscal 2023 and 65% last quarter. 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. Let me provide some context on Atlas consumption in the quarter.

As Dave mentioned, consumption growth in Q1 was above our expectations. This outperformance was broad-based and driven by stronger growth in underlying application usage.

While Q1 consumption trends were better than expected, the growth remains below the levels we experienced prior to the beginning of the slowdown in Q2 of last year.

Q1 consumption trends were better than expected. The growth remains below the levels we'd experienced prior to the beginning of the slowdown in Q2 of last year. Turning to Enterprise Advanced.

As you know, we'll be facing very difficult E.A. compares throughout fiscal 24, and Q1 was no exception as Evans by our slower year-over-year E.A. revenue growth.

However, EA revenues were up sequentially, which is better than what we'd anticipated in our Q1 guidance. This is despite the fact that Q1 is typically a seasonally slower new business quarter for EA.

Turning to customer growth. During the first quarter, we grew our customer base by approximately 2,300 customers sequentially, bringing our total customer count to over 43,100, which is up from over 35,200 in the year-ago period.

Of our total customer count, over 6,700 are direct sales customers, which compares to over 4,800 in the year-ago period.

As a reminder, our direct customer account growth is driven by customers who are net new to our platform, as well as self-serve customers with whom we've now established a direct sales relationship.

We saw a strong quarter of direct customer additions in our Enterprise channel. The growth in our total customer account is being driven primarily by Atlas, which had over 41,600 customers at the end of the quarter, compared to over 33,700 in the year-ago period. It is important to keep in mind the growth in our Atlas customer account reflects new customers to MongoDB.

In addition to existing EA customers adding incremental Atlas workloads.

We had another quarter with our net ARR expansion rate above 120%. We ended the quarter with 1,761 customers with at least $100,000 in ARR and annualized MRR which is up from 1,379 in the year of the period.

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

Gross profit in the first quarter was $279.9 million, representing a gross margin of 76%, which is up from 75% in the year ago period. We're very pleased with our gross margin progression, especially in the context of Atlas representing 65% of our overall business. We're very pleased with our gross margin progression, especially in the context of our overall business.

Our income from operations is $43.7 million, or a 12% operating margin for the first quarter, compared to a 6% margin in the year ago period. The primary reason for our strong operating income results versus guidance is our revenue out of performance.

In addition, Q1 benefited from the timing of marketing programs, internal events, and other expenses, which we now expect to incur later in the year.

Net income for the first quarter was $45.3 million or 56 cents per share based on 81.5 million diluted weighted average shares that's standing. This compares to net income of $15.2 million or 20 cents per share on 77 million diluted weighted average shares that's standing in the year ago period. Turning to the balance sheet and cash flow.

We ended the first quarter with $1.9 billion in cash, cash equivalence, short-term investments, and restricted cash. Operating cash flow in the first quarter was $53.7 million.

After taking the consideration of approximately $2 million in capital expenditures and principal repayments of finance lease liabilities, free cash flow was $51.8 million in the quarter.

This compares the free cash flow of $8.4 million in the first quarter of fiscal 2023. And now I'd like to turn to our outlook for the second quarter and full fiscal year 2024.

For the second quarter, we expect revenue to be in the range of $388 to $392 million. We expect non-gap income from operations to be in the range of $36 million to $39 million, and non-gap net income per share to be in the range of $0.43 to $0.46 based on $82.5 million estimated diluted weighted average shares outstanding.

For the full fiscal year 2024, we expect revenue to be in the range of $1.5 to $2 billion to $1.5 for $2 billion.

For the full fiscal year 2024, we expect non-gap income from operations to be in the range of $110 million to $125 million, and non-gap net income per share to be in the range of $1.42 to $1.56 based on 83 million estimated diluted weighted average shares outstanding.

Note that the non-GAP net income per share guidance for the second quarter and full year fiscal 2024 includes a non-GAP tax provision of approximately 20%.

And I'll provide some more context around our guidance starting with Q2. First I want to remind you that Q2 has three more days than Q1, which is a tailwind for Q2 Atlas revenue. And I'll provide some more context around our guidance starting with Q2.

Second, we expect to see a sequential decline in the EA business after a stronger than expected Q1. Third, we recently signed a few large licensing deals, most notably a renewal and extension of our relationship with Alibaba. Those deals have an upfront license revenue component, which will positively impact our revenue in Q2 by roughly $10 million.

You'll see this impact in other subscription revenues, the portion that is neither atlas nor EA.

Finally, we expect to see a significant sequential uptick in expenses since we have some of our largest sales and marketing events in Q2, most notably mongodb.local in New York. Turning to our updated full year guidance.

First, we are increasing our revenue expectations for the rest of the year because Atlas Q1 exit ARR is now higher than previously expected, given the stronger Q1 performance.

Second, we continue to expect that Atlas consumption growth will be impacted by the difficult macro environment throughout fiscal 24. Our revised full year revenue guidance continues to assume consumption growth that is in line with the average consumption growth we've experienced since the slowdown began in Q2 of last year. In other words, our usage growth assumptions for the remainder of the year remain unchanged.

from when we provided our initial guidance range for Fiscal 2024 last quarter.

Third, we continue to expect that the year-over-year growth of enterprise events will be impacted by the difficult compares from the prior year period.

Finally, thanks to strong Q1 performance and the increased revenue outlook.

We are meaningfully increasing our assumption for operating margins in Fiscal 24 to 7.7% at the midpoint of our guidance, an improvement of approximately 300 basis points compared to Fiscal 23, while continuing to invest to pursue our long term opportunity.

To summarize, MongoDB delivered strong first quarter results in a difficult environment. Our new business performance and strong total customer net additions demonstrate the continued demand for a developer data platform.

While we are pleased that Atlas Q1 consumption growth was above our expectations, we continue to be mindful of the environment. Taking a step back from the near-term trends, we're 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? Yes, sir. As a reminder, to ask a question, you will need to press star one one on your telephone. Again, that's star one one on your telephone to ask a question. We ask that you please limit yourself to one question and one follow-up.

Please stand by while we compile the Q&A roster.

Our first question comes from the line of Raimo Lynchau of Barclays. Your question please, Raimo.

Thank you. The first question before I have to follow on follow up question. If you know everyone talks about AI at the moment and Mongo in theory always kind of see you as an operational database. How do you fit into this kind of new AI world? You mentioned some of the names and some of the projects. It looks really exciting but.

But how does Mongo kind of fit into this new world? And I had one follow up from Mike.

Yes, sure, Raimau. First, we expect MongoDB to be a net beneficiary of AI. The reason being is that as developer productivity increases, the volume of new applications will increase, which by definition will create new apps, which means...

more data stores, so driving more demand for MongoDB. Second, developers will be attracted to modern platforms like MongoDB because that's the place where they can build these modern next generation applications. And third, because of the breadth of our platform and the wide variety of use cases we support, that becomes even more of an impetus.

We have a high degree of existing customers who are engaging with our field organizations on AI use cases.

And so the demand for using MongoDB to build and run these AI apps is very high.

Okay, perfect, thank you. And Michael, if I look at the update or the significant upgrade to the profitability outlook, like obviously you had your budgeting cycle to come up with the initial guidance. So what has changed besides maybe slightly higher revenue to kind of come up with these kind of much higher numbers? And obviously we all like that.

Okay, perfect. Thank you.

Thank you.

Our next question comes from the line of Sanjay Singh of Morgan Stanley . Your line is open, Sanjay.

Thank you for taking the questions and corrects to the MongoDB team on a strong start to the year. I wanted to start up with a question on the environment. As we talked, as we listened to the Hyper-TNV report, there results and seen some of the cloud infrastructure ecosystem report results. I would say we're all trying to get a sense of where are we in sort of the cloud optimization.

budget scrutiny sort of cycle. It sounded like, from what you guys are saying, that you guys are executing well, but things are still pretty tight from a budget environment perspective. I just wanted to get your latest perspective on whether you see Cloud Span and optimization headwinds.

fading anytime soon and what you saw in May, that potentially gave you maybe some leading indicators of where things may be headed.

Yes, so first point I'd make Sanjeev is that we don't really see optimization as a trend because there's a direct link between app usage and our revenue, right? So the more the apps are used, the more revenue that drives and consequently when apps are used less, the less revenue we get. And so there's a one-to-one correlation between usage and revenue which...

As you can imagine, when the customers are building these apps, they want their apps to be used. So that's really what's happening in terms of what's driving our revenue. In terms of what's happening in terms of the macro environment, I definitely agree with you that it's tough out there. But what we see is innovation is still a priority.

we see that customers really want to leverage software as a competitive advantage. We had very strong new business numbers. We added 2,300 customers this year. Our six-figure customer account grew 28% year over year. And our Atlas growth was 40% year over year. So like these are...

pretty good signs that customers are still prioritizing innovation and they're doing so leveraging modern platforms like MongoDB. So I would also say that our go-to-market channels have to really focus on and they're doing a really good job on qualifying these opportunities, being able to separate customers who are

serious versus customers who maybe just wanted to kick the tires. And again, as I mentioned earlier, it's all about us acquiring high quality workloads. If you can acquire high quality workloads on board them well and make sure the service well, good thing to happen. And that's happening. And we had a record number of new workloads added this quarter from existing customers.

I appreciate the perspective Dave. I just wanted to follow up on Rhyme's question on AI. And I guess the context is that you guys have proved that the document model has been very, very scalable in terms of addressing multiple different types of workloads and different data types. So in the context of...

large language model applications and customers trying to build applications with large language models and the roles of vectors and vector databases. From your guys' perspective, is this a use case that MongoDB can address and any sort of product updates or anything on the product roadmap to address this part of the market?

Right, so, and maybe I'll just do a little primer just so everyone's on the same page. The results that come from training an LLM against content are known as vector embeddings. And so content is assigned vectors and the vectors are stored in a database.

These databases then facilitate searches when users query, you know, a large language model with the appropriate vector embeddings. And it's essentially how a user's search is matched to content from an LLM. The key point though is that you still need an operational data store to store the actual data.

And there's some adjunct solutions out there that have come out that are bespoke solutions but are not tied to actually where the data resides. So it's not the best developer experience. And I believe that over time people will gravitate to a more seamless and integrated platform that offers a compelling user experience.

And I do want to say it's still very early days. I think people tend to overestimate the impact of new trends in the short term, but underestimate them in the long term. So it's very early days, and I think you're going to see a lot of things happening over the course of the next few months and quarters and years. But we feel we're in a very good position to take advantage of this new trend. I appreciate the comments. Thank you very much.

I think people tend to overestimate the impact of new trends in the short term, but underestimate them in the long term. So it's very early days. I think you're gonna see a lot of things happening over the course of the next, you know, few months and quarters and years. But we feel we're in a very good position to take advantage of this new trend. I appreciate the comments. Thank you very much. Thank you.

Our next question comes from the line of Brad Rebeck of Stiefel. Your question please, Brad. Great, thanks very much. Dave, last quarter you talked about a couple of very large financial institutions beginning to migrate. I believe it was hundreds of apps. I know you talked about better usage trends this quarter.

Did those migrations impact this quarter or is that more something you should expect in coming quarters? No, I mean, so one, we're obviously very happy about customers wanting to migrate a large percentage of their applications to MongoDB, but that takes time, right? It's not going to happen overnight. And so that's going to happen over the long term.

And so that's something that's a trend that we're feeling good about. I would say in terms of the usage trends, it's again tied to our customers' underlying business. And so the applications they're building on MongoDB are clearly being used. They're driving value, which consequently drives our revenue. And we feel really good and again.

So that drives us to go acquire more workloads, high quality workloads that we can then onboard quickly, and then that drives future usage. So that's the real focus for us, is let's focus on the input metrics that drive the outputs that you see. And that's example what happened this quarter. That's great. And then Michael, real quick, since the year got off to such a great start here, does it impact your hiring plans for the...

and believe that we can walk and chew gum at the same time.

That's great. Thanks very much. Thank you.

Thank you. Next question.

It comes from the line of Brent Breslin of Piper Sandler. Your question please, Brent.

Thank you. Dave, what drove the record number of new workloads migrating to the platform? You flagged that in the comments there. It seems a little too early for Gen AI to be driving the number of new workloads. What drove that? One quick follow-up as well. Thanks.

Yeah, like I said, I think people tend to overestimate the impact of a trend like AI in the short term. And so I would clearly say it wasn't AI that drove the acquisition of workloads. It was really sharp execution by go-to-market teams.

We have really focused our teams to acquire workloads, either through the acquisition of new customers or the acquisition of workloads in existing customers. It's all about acquiring workloads. So our incentive mechanisms, management attention, and focus is all about this North Star about acquiring new workloads. And I think you're seeing the results.

of that showing up in Q1. Great, blocking and tackling and walking one at two, sounds like it's working for you. My follow up is really around a vector feature engine as you think about AI. How important is layering in vector feature engines inside of the Mongo database.

Is that on the docket, how should we think about vector functionality inside of Mongo going forward relative to attracting more Gen AI workloads? Thanks.

Again, for generating content that's accurate in a performant way, you do need to use vector embeddings which are stored in a database. And you also need to store the data, and you want to be able to offer a very compelling and seamless developer experience.

and be able to offer that as part of a broader platform. I think what you've seen Brent is that there's been other trends, things like graph and time series where a lot of people got very excited about these kind of bespoke single function technologies but over time they got subsumed into a broader platform because it didn't make sense for customers.

strategy.

Looking forward to it. Thank you.

Thank you. Our next question comes from the line of Cash Rangan of Goldman Sachs. Your question, please, Cash. Thank you very much. Congratulations on the quarter. Great start to the year. One for David, one for Michael. You've talked about

big relational database displacements for a while now. So how are those deployments coming along, and are you increasingly able to open the door for even bigger deployments in the future? That's one for you, Michael. It now appears that you have a cadence where you, despite challenging consumption trends on a per customer basis, you've been able to...

add new customers at record pace. So results have been actually quite resilient. So how does this make you think about the business model ahead of me? Are you at a point where the new customer momentum more than offsets declining consumption growth trends that?

did you have better visibility into your business than you did probably, say, a year back, six months back or so? Thank you so much. Yeah, what I would say is, I think, you know, in the short term, the consumption trends are clearly tied to our customers' underlying business.

The only way we can really influence that is over the long term by acquiring more and more workloads, either from existing customers or acquiring new customers. And so we're really focused on what we can control, which is all about acquiring new customers and new workloads. And obviously there'll be puts and takes on every quarter, but our

go-to-market organization is very, very focused on this. And we do that not just from our sales organization, but also from our self-serve business. And then we also don't just focus on acquiring, but also making sure they're onboarded properly, they're serviced properly, so that those workloads grow well, and the customer's experience with those workloads is very positive, so they continue to add new workloads to our platform.

it's a new workload. It could be an existing workload that people want to replatform. We talked about the China Mobile example where it was a very, very large workload servicing a very, very large user population and they just weren't getting the performance benefits that they needed for such a large set of.

such a large implementation. So that was their catalyst to basically migrate to MongoDB. And I want to be clear, there's always gonna be some catalyst, gotta be some compelling event for a customer to do so. It could be for cost reasons, it could be for performance reasons like in China Mobile, or it could be that they can't add new features fast enough on a brittle legacy platform so they need to migrate to a new modern platform where they continue to service their own.

business well. So those are the drivers and that's a big focus for us as well.

So those are the drivers, and that's a big focus for us as well. Thank you.

first on the 10 million one-time lift from Alibaba, if you could just clarify the entirety of that lands in other subscription, none of it lands in Atlas or EA and is there any follow-through on that Alibaba or is it truly one-time

Q and then I've got a quick follow-up. Yeah, so it will show up, first of all, it's not just Alibaba in the 10 million but Alibaba is the one that you know people understand and know and we had a joint press release about and is certainly driving a healthy chunk of that.

It does show up in that kind of other other line. So it's not showing up in Atlas or in the EA line items just for sort of clarity around the geography. The extension of the deal, we initially signed a multi-year deal with them. This extends that contract.

The structure has minimum commitment levels. And so what runs through the P&L is the minimum commitment level. So obviously to the extent that there is outperformance above this, further increase level like that could impact things. We have seen those historically, that's part of what led to

the early renewal and extension given the success of the joint offering. Over the time since we've launched it, we've seen an 8x increase in their end-user consumption. That's what gave them and obviously us collectively the confidence to extend that.

Okay, great. Thanks, Mike. And then further on the 2Q Guide, the three extra days relative to Q1, does that loosely offer kind of an added, you know, three point sequential boost? And then secondly, in terms of the, you know, overall demand assumptions you're using to drive that 2Q Guide, is it...

its consumption and it's recognized as it's utilized. So that is a tailwind to Q2 relative to Q1 by those few extra days. In terms of the broader assumptions, the primary driver of the increase in the fiscal 24 full-year guide is the fact that Atlas outperformed in Q1, therefore are starting to move into

you know, get better or deteriorate further. And so it's consistent with our view that we had, you know, 90 days ago. Yep, super helpful. Thanks, Mike.

Thank you. Thank you. Thank you.

comes from the line of Tyler Radtke of Citi. Your question please, Tyler.

Yes, thanks very much for taking the question. So Dave, in your opening remarks, you talked about how AI can kind of provide a new opportunity for modernization of existing applications. I'm just curious from your perspective, how you see this playing out, when do you think this starts to accelerate the...

the pace in which companies modernize their apps and maybe how you're preparing your go-to-market team to tackle that opportunity. Yeah, Tyler, we're already seeing high customer engagement of customers already talking to us about new AI use cases that they want to build and run on MongoDB. So that's obviously a very positive trend. Again, it's early days so I don't want to...

suggest there will be some step function increase in consumption or revenue, but the trend is obviously real. As I mentioned, we already saw like over 200 customers who are AI companies who are you know deploying apps on MongoDB, and I would argue that you know there's an emerging trend that

Atlas is one of the preferred places for AI companies to go to build apps. And so we feel really good about our positioning. And I think we feel like it will be definitely a tailwind, given that with all the AI assist tools around co-generation and improving developer productivity, the capacity of a development team and a typical organization will only increase. For more information, visit www.lucas-de-hispania.com

statistics that say it can increase anywhere from 15 to 30, 40 percent. I think it's still early days to determine what percent is real, but it'll definitely increase, which by definition will increase the number of applications developed, which will then obviously drive more demand for MongoDB. That's helpful, and I assume the answer is too early, but as you look at those 200.

customers or so and maybe some existing ones that were already on the platform. Is there any way to think about quantifying the AI-related revenue or maybe where you think about that for the full year? I think it's way too early, Tyler. I think it's also really tied to the market and the product market fit of those customers' businesses because...

the next set of AI apps that they're building.

Thank you.

Thanks, Tyler.

Thank you. Our next question comes from the line of Jason Ader of William Blair. Your question please, Jason. Thank you. I just wanted to ask about the linearity of consumption.

through the quarter and then any comments you have on consumption in the month of May. Yeah, so I'd say, you know, clearly March and April were better than we expected, you know, given the outperformance of our revenue numbers and so that's, you know, great to see.

In general, what we've seen since the start of the slowdown is

Certainly some month to month variability, but in general, like some pretty reasonable ranges and to the extent that when we see

ranges that diverge, the start of Q2, the more pronounced holiday slowdown that we saw, we tend to call those out. But we feel that we've seen a pretty consistent level of sort of macro affected or post macro growth rates of existing expansion. That was what was included in our guide. And that's you know, what's initially for fiscal 24, and that's also what's in our guide for the balance of the year.

Okay, just yeah, I mean, what's a little hard to reconcile, as I understand the sort of one time pop in Q2, but for the back half, I mean, it just seems like growth is going to slow down massively.

year over year and just trying to understand.

If you're not assuming anything different on the macro, why would that be the case?

Yes, so what I would say is when we look at it, you've got a higher starting Q2 ARR as a result of the strong Q1 performance.

And as you flow through the same cohort expansion, for lack of a better phrase, over the balance of the year, that's what leads to the improved revenue outlook that we have. And so we're actually seeing, you know, stronger growth on a year-over-year basis for the back half of the year than we thought at the beginning of the year.

Got you. Then one quick last one for you, Michael, on the gross margin outlook. I think your long-term, unless it changed, I think it was 70 percent. You're running now in the mid-70s.

Seems like Atlas has really been above your expectations in terms of the gross margin. Any comments on just sort of like, you know, it's called the next couple years on gross margin?

Yeah, so we have not specifically guided the gross margin. You are correct. We have outperformed our expectations on gross margin. Our gross margin progression plan, particularly as it relates to Atlas, has been very strong. I would not have forecast.

such high gross margins with Atlas at almost two-thirds of our revenue. And so we've continued to execute incredibly well there. I would just go back to your comment around sort of our long-term target model was 70 plus. And so I think I feel significantly more confident in delivering against that now.

as we've kind of pulled additional levers, we've gotten more value out of the levers that we had identified along the way and that's what's put us in the strong position.

Thanks, guys. Thank you.

Our next question comes from the line of Fred Havemeyer of Macquarie Capital. Your question, please, Fred. Hey, thank you. I wanted to also follow up on margins with respect to Atlas. I think as your company is going through a transition from

Of course, more term licenses towards Atlas being more of a consumption-based model. It's exciting to see the margin upside flowing through as revenue is coming through, but I wanted, I think, a refresher on how to think about just essentially unit, sorry, just on how to think about margin progression with Atlas in play. Just generally once customers have signed and you are through that period of course Let's give the market?s all this show Android and usa iOS, or Linux Nortendez, with the Res concurrent

I think people understand that we have this very close value linkage and so it maps quite tightly to the underlying application usage for our customers and their end users. And so I think the key thing when you compare it to the 606 implications particularly of Enterprise Advance and the term license revenue is while it's not

ratable, and I do think sometimes there's the tendency to confuse what was ratable, it is spread over the duration if we just assume a one-year contract, which most of our contracts are. You know, you'll get the same revenue over time, but with the enterprise license, enterprise events license, you'll see that upfront revenue being lumpier, right? That's part of the reason why we talk about and go to great pains to explain that EA compares.

and some of those other things. So that's really the big driver. You get the same revenue, but there's less up front. I think the other thing that's important to understand in terms of financials.

is really the cash flow dynamics and understanding that. As we've talked about for the last several years, we've been de-emphasizing upfront commitments, trying to reduce the level of friction, trying to focus on acquiring more workloads and getting more workloads on the platform.

And the result of that is spending less time on upfront commitments. Atlas now has about 80% of Atlas does not flow through deferred. And so that's just a very different dynamic when you start thinking about less from the income statement, but more kind of away from the other parts of the balance sheet and some of the other calculations that you all do.

Thank you very much. Thank you. Our next question comes from the line of Kingsley Crane of Ken Accord.

Your question please Kingsley. Great, yeah so would like to ask a question about the replacement opportunity and in just a slightly different way. So we're all excited about this AI theme. I know this is more longer term but do you think that AI workloads creation and app replatforming can act as a catalyst.

And so it's a technology that's worked well for a long period of time, but it really doesn't suit the needs of modern applications. And as applications get more and more sophisticated, have more performance and scale requirements, people need to consider moving to more.

scalable platforms and that's our strength and you know China Mobile again is a great example of that and that's not even AI app. Okay great thank you.

Thank you once again to ask a question, please press star 11 on your telephone again that's star 11 on your telephone to ask a question. Our next question comes from the line of Michael Turret of KeyBank. Your line is open, Michael.

Hey guys, good evening. I want to come back to the usage trend. I want to maybe explain it, but I'm not sure. So what really drove the better than expected usage?

one Q. I know you said that execution was great which is awesome. I think of expectations for the rest of the year.

Sorry, say that last part of the question again, Michael. So what drove the better than expected usage in Q1, but then for the rest of the year, you're expecting a return to your prior assumptions regarding usage growth? Yeah, so let me try and clarify. So first, the strong execution I think that Dave was talking about really ties more to the new business environment, which remember is very valuable for the medium-to-low-level

And when you think about the, as I mentioned, there's a little bit of variability, you know, period to period, but other than sort of the start of the downturn in Q2 of last year and the more pronounced holiday slowdown, it's been in a fairly, you know, reasonable range.

That was the range that we've seen the performance in for Q1. That's the range that we saw the performance within our Q1, our guide at the beginning of the year for the full year. And so there's no real reason to change that outlook for the balance of the year. We're not assuming things get materially better. We're not assuming things get materially worse, and we don't have any data that would suggest either of those directions. And then just a quick follow-up. I know you talked about Atlas not running through deferred, but

You know, it's actually EA that was a little stronger this quarter. So what was maybe explained, but why did we see that sequential decline in deferred revenue that we haven't typically seen? Yeah, I go back to a couple of thoughts. One, billings in general is not a super helpful metric for us, and I know we've said that for really since going public, I guess.

But increasingly, I think that that is true. Certainly as roughly two thirds of the business is Atlas and as I mentioned about 80% of that does not flow through deferreds. But also what that means is that a larger portion of what will run through deferreds is EA. And you saw EA grew more slowly on a year of year basis and Q1 tends to be a seasonally slower quarter for new EA business.

Okay, all right, Mike and Dave, thanks very much. Thanks. Thank you. Our next question comes from the line of Mike Sikos of Needham. Your question please, Mike.

Hey guys, can you hear me all right? I apologize, the operator might have tuned out. Awesome. Uh, Jerry?

If I could just follow up on Michael's last question there and one of the things I wanted to highlight on that EA strength in Q1 I believe we were expecting EA to actually decline sequentially and you guys delivered some slight out performance there and I guess broadly if we look back over the last couple of quarters EA is

has really outperformed expectations. Can you help us think through what is driving that EA outperformance and I guess with more specific color Q1 where that outperformance came from?

Yeah, you have to, thanks for your question, Mike. You have to remember that one of our strengths is people can run MongoDB anywhere. And there's still a large percentage of workloads and a lot of customers who still run a lot of important workloads on-premise. I think the journey to the cloud is far from over. And the attraction of starting with MongoDB on-premise is that they, as a whole, the customers then get optionality.

Beyond that, obviously, more fun of all thing is people value MongoDB's ability to get the flexible document model, the highly distributed and scalable platform just gives enormous benefits whether it's on-prem or in the cloud. So that's something that people also value. So we still see a lot of demand. Obviously, Atlas is the biggest growth engine of our business, but there's still a lot of customers who lean into EA.

Yeah, I would just add, you know, we were expecting Enterprise Advance to be down and so the fact that it, you know, had a slight sequential gain, you know, it was great to see and speaks to all the points Dave is underscoring. I would just remind people that to the point, EA did have a very strong year last year and so we do face very difficult compares throughout the year.

The first, I know that you're really citing the SHARP execution from the go-to-market teams with respect to the number of new workloads or customer wins. One, if the sanity check, has relational migrator in any way played a role in landing these workloads and customers? That's the first part. The second part would be, can you just give us an update on how the investments are tracking as far as

enhancing features around time series and search capabilities on MongoDB. Yes, so on the first question, again, while we do have customers, some customers migrating relational workloads to MongoDB, I would not say relational migrate was a huge lever in making that happen. We're very excited by the prospects of relational migrate and helping to reduce the

the cost and time to migrate relational apps to MongoDB, but we're still early in that journey. With regards to time series and some of the other capabilities, we feel really good about the platform, uptake is high, and we plan to do a pretty broad set of announcements at our mongodb.local, New York, on June 22nd, so stay tuned for some announcements then.

That's great. I'll see you guys in New York in June . Thank you very much. Look forward to it. Thank you. Our next question comes from the line of Faraaz Belisi of Alliance Bernstein. Your question please, Faraaz.

Thank you for taking my question and congrats on a great quarter. Maybe the first one on the consumption trend.

So you have talked about revenue being linked to consumption and you have seen consumption level come down over the past three quarters. Is it fair to assume that in the next couple of quarters consumption level may reset at a new normal and then maybe resume growth from that level or is it hard to call bottom on the per user consumption level? Then I have a follow-up. Okay. Great, thank you.

Yeah, so what I'd say is we have...

I would just say when we look at our outlook, there's no reason based on the data that we have to assume that things get materially better or materially worse. And that's what's included in our guidance for the balance of the year. And that's consistent with what we thought in last quarter's call when we provided our initial view. And when we look at where we are now and the outlook, I think that's the right view. So, I don't think that there's any particular.

data that would point to things suddenly becoming better or becoming materially worse.

Got it. So recently we heard from another data platform vendor that they're seeing some of the customers move data out of the platform to maybe economize on cost. Are you seeing anything similar or do you see pockets of workloads where that might occur on MongoDB's platform as well?

Yes, so if I understood your question, you're saying are people moving, you've seen other companies have talked about customers moving data out of their platforms. We have not seen that trend. As we said, our consumption is tied to the application usage. And you have to remember, if a customer builds an application, they want that application to be used.

So the application is not being used in some ways. That's not a good thing for a customer. That being said, our revenue is driven by usage. So when usage goes up, our revenue goes up, and usage goes down, our revenue goes down. But it's very linked to the underlying trends of that customer's business. So the link from value to price is highly correlated. So we don't have customers who are, quote, unquote, trying to move data off.

That's not a phenomenon that we see. Thanks. Very helpful. Thank you. Our next question comes from the line of Howard Ma of Guggenheim Partners. Your question, please, Howard. Okay. Thank you. Excuse me, past the hour mark.

Can you can you just quickly comment on whether or not relational migrations are contributing more to growth relative to to to Greenfield plus subsequent expansion? And if you could frame that within the. The 2300 net ads in the quarter too. That'd be great. Thanks so much.

Yeah, sure. Thanks for the question, Howard. No, I would say generally consistent is what we've seen. I wouldn't particularly call out a particular spike up. Obviously, there's the China Mobile case study or vignette that Dave walked through, and you can always find those in every quarter. It continues to be a healthy part.

of the business, but I wouldn't uniquely call that out as sort of particularly, you know, driving the results, although it's obviously a big part of our long-term market opportunity. Okay, great. Thanks so much. Thank you. Thank you. I would now like to turn the conference back to Dave Itacharia for closing remarks, sir.

Thank you. I just want to again disclose by saying that we had another strong quarter new business performance while Atlas consumption rebounded from last quarter. We remain laser focused on Northstar, which is acquiring new workloads from both new and existing customers. We do believe AI will increase the velocity of software development and in turn increase the capacity of the new software.

the number and sophistication of new applications developed. And we believe that this will increase demand for powerful and comprehensive platforms like MongoDB over the long term. So with that, we wanna thank you for your time today and we look forward to seeing you on June 22nd at the Javits Center in New York City. Thank you.

This concludes today's conference call. Thank you for participating. You may now disconnect.

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