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. I would now like to hand the call over to Brian Denyeau with ICR. Please go ahead.

Great. Thank you, Latif. Good afternoon, and thank you for joining us today to review MongoDB's first quarter fiscal 2024 financial results, which we announced in our press release issued after the close of market today. Joining me on the call today are Dev Ittycheria, President and CEO of MongoDB; and Michael Gordon, MongoDB's COO and CFO. During this call, we will make forward-looking statements, 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 that could cause actual results to differ materially from our expectations. For a discussion of the material risks and uncertainties that could affect our actual results, please refer to the risks described in our Annual Report on Form 10-K for the year ended January 31, 2023, filed with the SEC on March 17, 2023. 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. Additionally, we will discuss non-GAAP financial measures on this conference call. 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 measures. With that, I'd like to turn the call over to Dev.

Thanks, Brian, and thank you to everyone for joining us today. I'm pleased to report that we had another strong performance in 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 MongoDB.local New York City to be held at the Javits Center on June 22. Please email [email protected] if you're interested in attending. Now turning to our results. We generated revenue of $368 million, a 29% year-over-year increase and above the high end of our guidance. Atlas revenue grew 40% year-over-year, representing 65% of revenue. And we had another strong quarter of customer growth, ending 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 and sharp execution by our go-to-market teams, who are navigating a difficult selling environment by remaining laser-focused on our North Star acquiring new workloads. In fact, this quarter, we acquired a record number of new workloads from our existing customers. 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 remained strong in Q1, reinforcing the enduring value of our platform. We are pleased with our results this quarter, especially given the difficult macro environment. It's clear customers continue to scrutinize our technology investments and must decide which technologies are a must-have versus a merely nice-to-have. We believe that our Q1 performance and continued new business strength demonstrate that MongoDB is clearly a must-have for customers. In today's digital economy, most companies express their business strategies 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 drive for innovation, making us a critical investment priority. Our customers, ranging from the largest companies in the world to cutting-edge startups, use our developer data platform to develop and run mission-critical applications. As these applications become successful, customers spend more with MongoDB. In other words, their spend on our platform is directly aligned with the usage of their underlying application, and 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 growth and MongoDB spend has remained consistent. We believe this is a testament to how well our value proposition is aligned to our customer 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 the competition. As I've said many times in the past, a durable competitive advantage is built through custom software; it cannot be obtained with an off-the-shelf product. Since most companies understand that they and 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. We believe AI will be the next frontier of developer productivity and will likely lead to a step-function 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. Said another way, if you are slow, then you're obsolete. Moreover, the shift to AI will favor modern platforms that offer a rich and sophisticated set of capabilities, delivered in a performance and scalable way. We are observing an emerging trend where customers are increasingly choosing Atlas as a platform to build and run new AI applications. For example, in Q1, more than 200 of the new Atlas customers were AI or ML companies. Well-financed startups like Hugging Face, Tekion, One AI, and Nuro 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 re-platformed 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 the technology that promises to accelerate the production of more applications and greater demand for operational data stores, especially those best suited for modern data requirements such as MongoDB. We look forward to telling you more at our Investor session on June 22. Now I'd like to spend a few minutes reviewing the adoption trends of MongoDB 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 Intuit are leveraging the power of our developer data platform. GE Healthcare has turned to MongoDB's developer data platform to manage the lifecycle of its IoT devices, imaging, ultrasound, and other patient-care devices from deployment to retirement. They selected Atlas for its effective management, scalability, built-in security, and multi-cloud support. GE Healthcare's use of Atlas helps healthcare providers enhance 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 their 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 Grant Thornton 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 its 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 bills to users. As a result, China Mobile migrated this service to MongoDB after comprehensive testing and evaluation of alternatives. By taking advantage of MongoDB's native sharding, they were able to improve performance by 80% and go from 50 Oracle machines to just 12 machines for the same workload. This service now handles all current requirements and is 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 the migration from on-premises to the cloud. Companies including Shutterfly, Radio, and Bendigo and Adelaide Bank are examples of customers leveraging MongoDB in their transformations. A leader in the HR and job-finding tech space shifted from MongoDB Community to MongoDB Atlas during its journey to migrate its entire infrastructure from on-premises to the cloud. They selected MongoDB Atlas to give their 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 their migration journey to Atlas, the company identified significant infrastructure reduction and subsequent cost savings. In addition, the company has experienced 250% faster query performance and 300% faster write throughput on their applications built on Atlas. In summary, I'm 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 opportunities. With that, here's Michael.

Thanks, Dev. As mentioned, we delivered a strong performance in the first quarter, both financially and operationally. I'll begin with a 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 Dev 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 that 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 Dev 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 had experienced prior to the beginning of the slowdown in Q2 of last year. Turning to Enterprise Advanced. As you know, we will be facing very difficult EA compares throughout fiscal 2024, and Q1 was no exception as evidenced by our slower year-over-year EA revenue growth. However, EA revenues were up sequentially, which is better than what we had 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 count 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 count 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 that growth in our Atlas customer count reflects new customers to MongoDB in addition to existing EA customers adding incremental Atlas workloads. We had another quarter with our net expansion 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-ago period. Moving down the income statement. I'll be discussing our results on a non-GAAP 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. Our income from operations was $43.7 million, or 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 outperformance. 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 $0.56 per share based on 81.5 million diluted weighted average shares outstanding. This compares to net income of $15.2 million or $0.20 per share on 77 million diluted weighted average shares outstanding 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 equivalents, short-term investments, and restricted cash. Operating cash flow in the first quarter was $53.7 million. After taking into consideration 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 to free cash flow of $8.4 million in the first quarter of fiscal 2023. I'd now 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 million to $392 million. We expect non-GAAP income from operations to be in the range of $36 million to $39 million and non-GAAP 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 billion to $1.542 billion. For the full fiscal year 2024, we expect non-GAAP income from operations to be in the range of $110 million to $125 million, and non-GAAP 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-GAAP net income per share guidance for the second quarter and full year fiscal 2024 includes a non-GAAP tax provision of approximately 20%. I'll now 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. 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 will 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 2024. 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 what we provided our initial guidance range for fiscal 2024 last quarter. Third, we continue to expect that the year-over-year growth of Enterprise Advanced 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 2024 to 7.7% at the midpoint of our guidance, an improvement of approximately 300 basis points compared to fiscal 2023, 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 our 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 are 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.

Yes, sir. Our first question comes from the line of Raimo Lenschow of Barclays. Your question please, Raimo.

Thank you. My first question is about how Mongo fits into the current AI landscape, especially since everyone is discussing AI right now and Mongo is typically seen as an operational database. You mentioned some interesting names and projects, but I would like to know how Mongo integrates into this new world. I also have a follow-up question for Michael.

Sure, Raimo. 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, 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 to use MongoDB. As I mentioned that we've had over 200 customers just in the last quarter running AI apps on Atlas. Some of those include some very cutting-edge, well-financed startups like Nuro, Hugging Face, and Tekion. We have a high degree of existing customers who are engaging with our field organizations on AI use cases. 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, obviously you had your budgeting cycle to come up with the initial guidance. So what has changed besides maybe slightly higher revenue to come up with these much higher numbers? And obviously, we all like that. But what drove that? Thank you and congrats from me.

Thanks. Yes. The big driver of the improved bottom-line output is the stronger Q1 performance and then the upgraded revenue outlook, and it's really just sort of flowing through to the P&L.

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

Thank you for taking the questions and congrats to the MongoDB team on a strong start to the year. I wanted to start off just a question on the environment. As we listen to the hyperscalers report, their results seem some of the cloud infrastructure ecosystem reported results. We're all trying to get a sense of where we are in the cloud optimization budget scrutiny cycle. It sounded like from what you guys are saying that you are executing well, but things are still pretty tight from a budget environment perspective. So wanted to get your latest perspective on whether you see cloud spend and optimization headwinds fading anytime soon? And then what you saw in May that potentially gave you some leading indicators on where things may be headed?

Yes. The first point I'd make, Sanjit, is that we don't really see optimization as a trend because there's a direct link between app usage and our revenue. The more the apps are used, the more revenue that drives. 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 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 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 count grew 28% year-over-year, and our Atlas growth was 40% year-over-year. So these are pretty good signs that customers are still prioritizing innovation and they're doing so leveraging modern platforms like MongoDB. Our go-to-market channels have to really focus on qualifying these opportunities, being able to separate customers who are serious versus customers who may just want to kick the tires. It's all about us acquiring high-quality workloads. If we can acquire high-quality workloads, onboard them well and make sure they're served as well, good things will happen; and that's happening. We had a record number of new workloads added this quarter from existing customers.

I appreciate the perspective, Dev. I just wanted to follow up on Raimo's question on AI. And I guess the context is that you have proven that the document model has been 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 rules of vectors and vector databases, from your 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, let me just frame it for everyone. The results that come from training and LLM against content are known as vector embeddings. Content is assigned vectors and the vectors are stored in a database. These databases then facilitate searches when users query large language models with the appropriate vector embeddings, and it's essentially how a user searches match to content from an LLM. The key point, though, is that you still need an operational data store to store the actual data. There are some adjunct solutions out there that have come out that are bespoke solutions but are not tied to where the data resides, so it's not the best developer experience. I believe that over time, people will gravitate to a more seamless and integrated platform that offers a compelling user experience. 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. 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, Dev. Thank you very much.

Thank you. Our next question comes from the line of Brad Reback of Stifel. Your question please, Brad.

Thank you, Dev. Last quarter, you mentioned that several large financial institutions were starting to migrate hundreds of apps. You also discussed improved usage trends this quarter. Did those migrations have an impact this quarter, or are we likely to see the effects in the upcoming quarters?

We are very pleased that customers want to migrate a significant portion of their applications to MongoDB, but this process takes time and will not occur immediately. It's a long-term trend that we're optimistic about. Regarding usage trends, they are tied to our customers' core business. The applications developed on MongoDB are clearly being utilized and generating value, which in turn boosts our revenue, and we feel very positive about this. This motivates us to seek out more high-quality workloads that we can onboard swiftly, which will drive future usage. We are concentrating on the input metrics that lead to the outputs you observe, and this is reflective of what transpired 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 rest of this fiscal year? Thanks.

Yes, thanks for the question, Brad. Yes. Strong start to the year, no major changes. Obviously, all that's factored into the full-year guide, and you can see the significant upgrade in the bottom-line outlook. We are continuing to invest for the long term, though, and believe that we can walk and chew gum at the same time.

Thank you. Our next question comes from the line of Brent Bracelin of Piper Sandler. Your question please, Brent.

Thank you. Dev, 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, so what drove that?

Like I said, I think people tend to overestimate the impact of a trend like AI in the short term. 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 are all about this North Star about acquiring new workloads. I think you've seen the results showing up in Q1.

Great, blocking and tackling, and walking while chewing gum. 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 that are stored in a database. But you also need to store the data, and you want to be able to offer a very compelling and seamless developer experience, as part of a broader platform. I think what you've seen is that there's been other trends, things like graph and time series, where a lot of people are 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 to have all these bespoke solutions, which added so much complexity to their data architecture. I don't want to preempt what we're going to be talking about on June 22, but I encourage you to attend because that's where we'll share a little bit about our AI strategy.

Looking forward to it. Thank you.

Thank you. Our next question comes from the line of Kash Rangan of Goldman Sachs. Your question, please, Kash.

Thank you very much. Congratulations on a successful quarter and a great start to the year. I have a question for Dev and another for Michael. Dev, you have discussed the progress of database displacements for some time now, so I would like to know how those deployments are progressing. Are you finding it easier to secure even larger deployments in the future? And Michael, it seems you have established a regular pattern where, despite challenging consumption trends per customer, you have been able to acquire new customers at an unprecedented rate, making your results quite strong. How does this influence your view of the business model going forward? Are you at a stage where the momentum from new customers compensates for the decline in consumption growth, and do you have better visibility into your business now compared to a year or six months ago? Thank you.

What I would say is, 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. We're really focused on what we can control, which is all about acquiring new customers and new workloads. Obviously, there'll be puts and takes in every quarter, but our go-to-market organization is very focused on this. We do that not just from our sales organization but also from our self-serve business. We not just focus on acquiring, but also make sure they're onboarded properly and 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. You talked about...

I appreciate it.

We are recognizing that part of acquiring a workload involves taking on a relational workload and re-platforming it on MongoDB. When we mention acquiring a workload, it should not always be assumed that it is a new workload; it could also be an existing workload that needs to be re-platformed. We discussed the China Mobile case, which involved a significant workload servicing a vast user base. They weren't achieving the required performance benefits for such a large implementation, which prompted their decision to migrate to MongoDB. I want to emphasize that there is always a catalyst involved. A customer needs a compelling reason to make the transition, which could be related to cost, performance issues like those faced by China Mobile, or the inability to add new features quickly on a fragile legacy platform, necessitating a shift to a modern platform that can better support their business. These are the factors driving these decisions, and they remain a crucial focus for us.

Thank you. Our next question comes from the line of Karl Keirstead of UBS. Your question please, Karl.

Thank you. Maybe this will go to Mike. Mike, if we could unpack the 2Q guide a little bit. 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, or is it truly one-time 2Q?

Yes. First of all, it's not only Alibaba involved in the $10 million, but Alibaba is the recognizable name, and we had a joint press release about it. It certainly accounts for a significant part of that amount. It appears in the "other" category, so it is not included in Atlas or EA for geographical clarity. The extension of the deal is a continuation of a multiyear agreement we initially signed with them. This extends that contract, and the structure includes minimum commitment levels. Therefore, what affects the profit and loss statement is the minimum commitment level. If there is any performance above this increased level, that could have an impact. We have observed such occurrences historically. This was part of the reason for the early renewal and extension, thanks to the success of our joint offering. Since we launched it, we've seen an eightfold increase in their end-user consumption, which gave both them and us the confidence to extend the deal.

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 three-point sequential boost? And then secondly, in terms of the overall demand assumptions you're using to drive that 2Q guide, is it sort of similar broader trends that you've seen in the last couple of months? Or Mike, are you assuming things get better or things get a little worse? Thanks. And that's it for me.

Yes. So you're correct. Q2 days, it does affect because it's consumption and it's recognized as it's utilized. So that is a tailwind to Q2 relative to Q1 by those few extra days. The primary driver of the increase in the fiscal 2024 full-year guide is the fact that Atlas outperformed in Q1. Therefore, our starting Atlas ARR for Q2 is higher. We have not changed our outlook for the expected growth over the balance of the year. So, we're not seeing things get worse. We're not assuming things get better or deteriorate further, so it’s consistent with our view that we had 90 days ago.

Thank you. Our next question comes on the line of Tyler Radke of Citi. Your question please, Tyler.

Thank you for taking my question. Dev, in your opening remarks, you mentioned that AI presents a new opportunity for modernizing existing applications. I'm interested in your perspective on how you see this developing. When do you believe this will start to speed up the pace at which companies modernize their apps? Also, how are you preparing your go-to-market team to seize this opportunity?

Yes. Tyler, we're already seeing high customer engagement. Customers are 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. It's early days, so I don't want to suggest that there will be some step function increase in consumption or revenue, but the trend is real. We already saw over 200 customers who are AI companies deploying apps on MongoDB. I would argue that there's an emerging trend that Atlas is one of the preferred places for AI companies to go to build apps, and we feel really good about our positioning. We feel like it will be a tailwind since all the AI assist tools around co-generation and improving developer productivity increase development capacity in typical organizations, with statistics suggesting 15% to 40% increases. It's still early days to determine what percent is real, but it will definitely increase, which by definition will increase the number of applications developed, driving more demand for MongoDB.

That's helpful. 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 where you think about that for the full year?

I think it's way too early, Tyler. It's also really tied to the market and the product market fit of those customers' businesses because obviously, if those customers do well, then we're a beneficiary. If they're not doing well, then they're not going to drive a lot of consumption. It's really tied to the product market fit of those companies, but the general trend we are pleased about is that a lot of people are leaning toward MongoDB in terms of thinking about the next set of AI apps that they're building.

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 any comments you have on consumption in the month of May?

Yes. I'd say clearly March and April were better than we expected given the outperformance of our revenue numbers. In general, what we've seen since the start of the slowdown is some month-to-month variability but mainly some reasonable ranges. That was the range we saw in our Q1 guidance for the full year. 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.

Okay, yes. What's a little hard to reconcile is that I understand the one-time increase in Q2, but for the second half, it just seems like growth is going to slow down significantly year-over-year. I'm just trying to understand. If you're not expecting anything different in the macro environment, why would that be the case?

When we look at it, you've got a higher starting Q2 ARR due to the strong Q1 performance. As you flow through the same cohort expansion over the balance of the year, that's what leads to the improved revenue outlook that we have. We're actually seeing stronger growth on a year-over-year basis for the back half of the year than we thought earlier in the year.

Thank you. Our next question comes from Fred Havemeyer of Macquarie Capital. Your question please, Fred.

Thank you. I wanted to follow up on margins related to Atlas. As your company transitions from more term licenses to a consumption-based model with Atlas, it's encouraging to see the margin improvement as revenue increases. However, I would like some clarification on how to understand margin progression with Atlas. Specifically, after customers sign and you complete the period for recognizing commissions, how should we view the incremental revenue from Atlas in terms of its effect on profitability?

Sure. Generally, what you see is Atlas revenue is consumption-oriented. We have this very close value linkage, so it maps tightly to the underlying application usage for our customers and their end users. The key thing to understand when you compare it to the 606 implications of enterprise advanced is that Atlas is not ratable; it is spread over the duration. In terms of the financials, the dynamics of cash flow and understanding are important. We've been deemphasizing upfront commitments, trying to reduce friction, focusing on acquiring more workloads. About 80% of Atlas does not flow through deferred, so that's a different dynamic when thinking about the balance sheet and those calculations.

Thank you. Our next question comes from Kingsley Crane of Canaccord. Your question please, Kingsley.

Great. Yes. So I would like to ask a question about the replacement opportunity and just slightly differently. We're all excited about this AI theme. I know this is a long-term trend, but do you think that AI workloads creation and app replatforming can act as a catalyst for share shifts as relational databases are less prepared to support these workloads?

I think, over the long term, that's definitely the case. People forget that the relational database has been around for almost 45 years, right? It's a technology that has worked well for a long period, but it really doesn't suit the needs of modern applications. As applications get more sophisticated and have more performance and scale requirements, companies need to consider moving to more scalable platforms, and that's our strength. China Mobile, again, is a great example of that. And that's not even AI apps.

Thank you. Our next question comes from the line of Michael Turits of KeyBanc. Your line is open, Michael.

Hi, everyone. Good evening. I would like to revisit the usage trends. Can you explain what contributed to the better-than-expected usage in Q1? I understand you mentioned that execution was excellent, which is great. What are the expectations for the remainder of the year?

What I'd say is the strong execution ties more to the new business environment, which remember is valuable for the medium to long term. The near term is tied to the performance of existing applications. What drove the outperformance was stronger underlying usage of those applications. We feel that we've seen a consistent level of growth rates related to macro-affecting existing expansion. That was included in our guide and is our guide for fiscal 2024 and the balance of the year.

Thank you. Our next question comes from the line of Mike Cikos of Needham. Your question please, Mike.

Hi, guys. Can you hear me all right? I apologize. The operator might have tuned out.

Yes, all good, no problem.

Awesome. If I could just follow up on Michael's last question there. 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 outperformance there. Can you help us think through what is driving that EA outperformance; and I guess, with more specific color to Q1, where that outperformance came from?

Yes. You have to remember that one of our strengths is people can run MongoDB anywhere. There's a large percentage of workloads and customers who still run important workloads on-prem. The journey to the cloud is far from over. Starting with MongoDB on-prem gives customers the optionality to move to the cloud later. That is a very attractive part of our value proposition. Beyond that, people value MongoDB's ability with a flexible document model. The highly distributed and scalable platform provides enormous benefits whether on-prem or in the cloud. That's something people value, and we still see a lot of demand. Obviously, Atlas is the biggest growth engine of our business, but there are still many customers leaning into EA.

We were expecting enterprise advanced to be down. So the slight sequential gain is great to see and speaks to all the points Dev is underscoring. I would remind people that EA did have a very strong year last year, so we do face difficult compares throughout the year on enterprise advanced.

Thank you. Our next question comes from the line of Firoz Valliji of Alliance Bernstein. Your question, please, Firoz.

Hi. Thank you taking my question, and congrats on a great quarter. Maybe the first one on the consumption trends. So you have talked about revenue being linked to consumption. We have seen consumption levels come down over the past few quarters. Is it fair to assume that in the next couple of quarters consumption levels may reset at a new normal and then maybe resume growth from that level? Or is it hard to call the bottom on the per-user consumption level? And then I have a follow-up. Thank you.

Yes. What I'd say is we have no reason based on the data we have to assume things get materially better or materially worse, and that's also consistent with what we thought in last quarter's call when we provided our initial view.

Got it. And so recently, we heard from another data platform seeing some customers move data out of the platform to economize on costs. Are you seeing anything similar? Or do you see pockets of workloads where that might occur on MongoDB's platform as well?

If I understood your question, you're saying are people moving data off their platforms. We have not seen that trend. Our consumption is tied to the application usage. Remember, if customer builds an application, they want that application to be used, so if the application is not being used, that's not good for a customer. Our revenue is driven by usage, so when usage goes up, our revenue goes up. When usage goes down, our revenue goes down, but it's linked to the underlying trends of that customer's business, so the link from value to price is highly correlated.

Thank you. Our next question comes from the line of Howard Ma of Guggenheim Partners. Your question please, Howard.

Thank you for squeezing me in off the hour mark. Can you just quickly comment on whether relational migrations are contributing more to growth relative to greenfield plus subsequent expansion? If you could frame that within the 2,300 net adds in the quarter too, that would be great. Thank you.

Generally consistent is what we've seen. I wouldn't call out a particular spike up. There are customers migrating relational workloads to MongoDB, but I wouldn't say relational migrator was a huge lever in making that happen. We're excited about its prospects, but we're still early in that journey. The healthcare story shows that there's continued demand for our platform.

Thank you. I would now like to turn the conference back to Dev Ittycheria for closing remarks. Sir?

Thank you. I just want to again close by saying that we had another strong quarter of new business performance, while Atlas consumption rebounded from last quarter. We remain laser-focused on our North Star, 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, the number and sophistication of new applications developed. We believe that this increase will drive demand for powerful and comprehensive platforms like MongoDB over the long term. Thank you for your time today, and we look forward to seeing you on June 22 at the Javits Center in New York City.

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