MongoDB, Inc.

Good day and thank you for standing by. Welcome to the MongoDB's Q1 FY26 earnings conference call. At this time, all participants are in listen-only mode. Please be advised that today's conference is being recorded. After the speaker's presentation, there will be a question and answer session. To ask a question, please press star 1 1 on your telephone and wait for your name to be announced. To withdraw your question, please press star 1 1 again. I would now like to hand the conference over to your speaker today, Brian Denue from ICR. Thank you, Josh.

Good afternoon, and thank you for joining us today to review MongoDB's first quarter fiscal 2026 financial results, which we announced in our press release issued after the close of market today. Joining me on the call today are Dave Itacheria, President and CEO of MongoDB, and Mike Berry, CFO of MongoDB. During this call, we will make four looking statements, including statements related to our market and future growth opportunities, our opportunity to win new business, our expectations regarding Atlas consumption growth, the impact of non-Atlas business and multi-year license revenue, the long-term opportunity of AI, the opportunity of application modernization, our expectations regarding our win rates and Salesforce productivity, our financial guidance and underlying assumptions, and our planned share repurchases and investments and growth opportunities in AI. These statements are subject to a variety of risks and uncertainties, including the results of operations and financial condition, They 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 risk described in our annual report on Form 10-K for the year ended January 31st, 2025, filed with the SEC on March 20th, 2025. Any forward-looking statements made in this call reflect our views only as of today, and we undertake no obligation to update them except as required by law. Additionally, we'll discuss non-GAAP financial measures in 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 the most directly comparable GAAP financial measure. With that, I'd like to turn the call over to Dave.

Thank you, Brian, and thank you to everyone joining us today. I'm pleased to report that we got off to a strong start in fiscal 2026 as we executed well against a large market opportunity. Let's begin by reviewing our first quarter results. before giving you a broader company update. We generated revenue of $549 million, a 22% year-over-year increase and above the high end of our guidance. Atlas revenue grew 26% year-over-year, representing 72% of revenue. We generated non-GAAP operating income of $87 million for a 16% non-GAAP operating margin, and we ended the quarter with over 57,100 customers. Overall, we posted a strong Q1 despite a dynamic and fast-changing macro environment. We had a solid new business quarter. We are beginning to see the benefit of our decision to focus our resources on the high end of the market, where we have the largest opportunity. Atlas consumption this quarter played out in line with our expectations. Mike will discuss consumption trends in more detail and our expectations for the remainder of the year. Our total customer net ads are the highest in over six years, reflecting the continued strong adoption of MongoDB across a wide range of industries and use cases. Self-serve customer additions were particularly strong this quarter, reinforcing MongoDB's position as the go-to platform for developers building the next generation of applications, including many focused on AI. While these accounts typically start small, the self-serve channel is a powerful engine for long-term growth. Finally, retention rates remain strong in Q1, demonstrating the quality of our product and the mission criticality of our platform. We are pleased with our Q1 performance. As I said before, companies leverage software to execute their business strategy, drive differentiation, and improve operational efficiency. As the operational database that is the core of software applications, MongoDB is undeniably a must-have component of the tech stack. We continue to make progress toward our goal of becoming the standard platform for enterprises and the default for developers building new applications. At the heart of this momentum is MongoDB's modern architecture, which delivers real and measurable advantages for the types of applications being built today, cloud native, distributed, real-time, and the AI-powered applications of tomorrow. MongoDB's document model and the associated platform enables developers to more easily represent the messiness of real-world data, which includes understanding relationships between structured and unstructured data, and managing data that is constantly evolving and changing. This fundamental architectural advantage provides customers greater flexibility, faster time to market, and the ability to scale without re-architecting. These capabilities are why customers continue to develop more and more mission-critical workloads in MongoDB, illustrated by our strong customer additions this quarter. As AI redefines how applications are built and how businesses operate, MongoDB is exceptionally well-positioned. Real-world AI applications require high quality, context-rich, and offer unstructured data to deliver trustworthy outputs. We continually hear from large enterprises that high accuracy is a critical requirement to drive wide-scale adoption of AI. Our recent acquisition of Voyage AI enhances our ability to serve this need. Embeddings are the bridge between a large language model and a customer's private data. Voyage's leading embedding and re-ranking models allow customers to feed precise and relevant context into LLMs, significantly improving the accuracy and reliability of the output of AI applications. By producing the most contextually rich domain-optimized embeddings, MongoDB sits at a gateway of meaning in an AI system. With the release of Voyage 3.5, we've taken another step forward, meaningfully outperforming the next best embedding models while reducing storage costs by more than 80%. This makes it not only powerful, but also cost-effective at scale. So what does this all mean? MongoDB now brings together three things that modern AI-powered applications need, real-time data, powerful search, and smart retrieval. By combining these into one platform, We make it dramatically easier for developers to build intelligent, responsive apps without stitching together multiple systems. In their desire to keep up with evolving customer needs, some vendors are retrofitting their products, such as adding JSON or vector support, as afterthoughts, which are superficial and brittle. This is a tacit admission that MongoDB's approach of using JSON and the document model is the best way to model real-world data. These features may check the box, but they fall apart in production, leading to performance bottlenecks, operational headaches, and spiraling infrastructure costs. Fundamentally, these vendors are constrained by the relational underpinnings. It's important to understand that superficial compatibility with modern data types is not the same as deeply integrated production-grade functionality. MongoDB, by contrast, was purpose-built to address these needs natively. We see this dynamic in our customer base every day. To bring this to life with an example, Zepto, an India-based quick commerce platform with 1.5 billion annual sales, migrated to MongoDB from Postgres after experiencing scalability challenges. Zepto offers users a choice of over 15,000 products with a promised 10-minute delivery and has grown rapidly since its founding in July 2021, recording 20% month-over-month growth. After this rapid growth, Zepto faced performance issues with its previous infrastructure powered by Postgres and Redis clusters that could no longer scale. By migrating to MongoDB Atlas, Zepto overcame these challenges through built-in features like in-memory caching, sharding, and real-time analytics. This transition enabled them to reduce latency by 40%, handle six times more traffic, and improve page load times by 14%, directly enhancing customer experience and enabling their fast growth. As we look ahead, we're confident MongoDB's combination of architectural advantage, enterprise trust, and broad developer adoption positions us to lead in both the current wave of digital transformation and the next wave powered by AI. We also remain focused on our other strategic priorities we've discussed in previous quarters, moving up market and modernizing legacy apps. We're seeing good progress on these initiatives, which will fuel growth into fiscal 27 and beyond. This quarter, we hired a new leader who has nearly 30 years of experience in technology transformation at Leading Systems Integrators to lead our application modernization program. We continue to see significant demand to modernize legacy applications and we're making great progress on tooling to automate this effort to standardize and productize this offering. While we continue to invest in the long term, we are also sharpening our focus on operating efficiency. We view this as healthy discipline, regularly reassessing the return on our spend, identify what's working and what's not, and reallocating resources to high conviction areas and improving profitability. To help usher in our next stage of growth, I'm delighted to introduce two new leaders to the executive team. Mike Berry, our new CFO, joins us from NetApp, where he has served in the same role for the past five years. Mike is a seven-time CFO with over 30 years' experience in technology and software and has a proven track record of driving profitable growth. We have also promoted May Petrie to be our new CMO. May joined MongoDB in early 2022 as VP of Digital and Growth Marketing and brings the right mix of enterprise experience and results orientation to lead our marketing organization. Now I'd like to spend a few minutes reviewing the adoption trends of MongoDB across our customer base. Customers across industries and around the world are running mission-critical projects in Atlas, leveraging the full power of our platform, including the European Commission, Lenovo, Nokia Networks, and CSX. CSX, a leading U.S. railroad transportation company, migrated its mission-critical Railroad Transportation Operations Portal, which is responsible for real-time monitoring and alerts across 21,000 miles of track and ensuring uninterrupted 24x7 availability onto MongoDB Atlas. CSX can now dynamically scale workloads and optimize the database management. With this modernization, CSX is positioned to achieve greater operational performance while driving long-term sustainable growth. Startups and mature companies are using MongoDB to help to deliver the next wave of AI-powered applications to their customers, including Cursor, Halion, Vonage, the Financial Times, and LG U+. LG U+, a South Korean mobile network operator owned by the LG Corporation, built its agent-assist AI solution on MongoDB Atlas, which supports thousands of agents in accessing information and delivering accurate responses to customers quickly. They use MongoDB Atlas Vector Search to enable real-time AI capabilities, such as identifying customer intent and providing guidelines on how to respond to inquiries. The solution has significantly enhanced customer experiences and decreased the average processing time per call. In summary, we had a strong Q1 and we remain confident in our ability to execute on a long-term opportunity. We're steadily advancing toward a vision of becoming the go-to platform for enterprises and the first choice for developers creating new applications. Before I turn it over to Mike, I would personally invite you to the investor session at the mongodb.localnyc to be held at the Javits Center on September 17th. Please email ir at mongodb.com if you're interested in attending. With that, here's Mike.

Thank you, Dave, for that great introduction. I am thrilled to join MongoDB at such an exciting moment in its growth journey. The company's incredible track record of product innovation and established leadership position in one of the largest, most strategic markets in software provides significant growth drivers that we expect to benefit our business for years to come. The opportunity to join a company the caliber of MongoDB was incredibly compelling. I would like to thank Dave and the entire board for giving me this opportunity. I am extremely excited and look forward to working alongside the talented team to create long-term value for our customers, shareholders, and employees. Driving profitable growth with operational excellence and discipline is a priority for the whole leadership team. With that said, let's move on to the financial results. I'll begin with a detailed review of our first quarter results and then finish with our outlook for the second quarter and fiscal year 26. I will be discussing our results on a non-GAAP basis unless otherwise noted. In the first quarter, total revenue was $549 million, up 22 percent year-over-year and above the high end of our guidance. Shifting to product mix, Atlas grew 26 percent in the quarter compared to the year-ago period and now represents 72 percent of total revenue. This compares to 70 percent in the first quarter of fiscal 25 and 71 percent last quarter. Let me provide some context on Atlas consumption in the quarter. In Q1, consumption growth was in line with our expectations. Given the unique macroeconomic backdrop, I will provide some detail on the month-over-month trends, but please note that I do not expect to give this level of detail going forward. Specifically, we saw good consumption growth in February and March, some softness in April as macroeconomic volatility increased, followed by a healthy rebound in May. Turning to non-Atlas, revenue came in ahead of our expectations in the quarter as we continued to have success selling incremental workloads into our existing EA customer base. Turning to customer growth, during the first quarter, we grew our customer base by approximately 2,600 sequentially, bringing our total customer count to over 57,100, which is up from over 49,200 in the year-ago period. The growth in our total customer count is being driven primarily by Atlas, which had over 55,800 customers at the end of the quarter, compared to over 47,000 700 in the year-ago period. It is important to keep in mind that the growth in our Atlas customer count reflects new customers to MongoDB in addition to existing EA customers deploying workloads on Atlas for the first time. Of our total customer count, over 7,500 are direct sales customers, relatively flat the last quarter and up 5% year-over-year. These metrics are largely due to our decision to reallocate a portion of our go-to-market resources from the mid-market to the enterprise channel starting in the second half of last year. We expect this dynamic will continue going forward as we capture more mid-market customers with our self-serve motion. In Q1, our net AR expansion rate was approximately 119 percent, which is consistent with recent quarters. We ended the quarter with 2,506 customers with at least $100,000 in ARR, a 17% growth versus the year-ago period. Moving down the income statement, gross profit in the first quarter was $407 million, representing a gross margin of 74%, which is down from 75% in the year-ago period. Our year-over-year gross margin decline is primarily driven by Atlas growing as a percent of the overall business and the impact of the voyage acquisition. Our income from operations was $87 million for a 16 percent operating margin compared to a 7 percent operating margin in the year-ago period. We are very pleased with our stronger-than-expected operating margin results, which benefited from our revenue outperformance as well as the timing of expenses, particularly slower than planned headcount additions. Net income in the first quarter was $86 million, or $1 per share, based on 86 million diluted shares outstanding. This compares to a net income of $43 million, or 51 cents per share, on 83 million diluted shares outstanding in the year-ago period. Turning to the balance sheet and cash flow, we ended the quarter with $2.5 billion in cash, cash equivalents, short-term investments, and restricted cash. Operating cash flow was $110 million, and free cash flow was $106 million in the first quarter, which compares to $64 and $61 million, respectively, in the year-ago period. The strong start for cash flow in fiscal 26 was driven primarily by strong operating profit results and higher cash collections. Before turning to our outlook in greater detail, I would like to share the key points driving how we are looking at the rest of fiscal year 26. Number one, we are raising our expectations for revenue based on our strong start to the year. Number two, We are increasing our operating margin guidance by 200 basis points, reflecting an increased focus on margin improvement. And number three, we are announcing a significant expansion to our share repurchase program. I would like to take a minute to provide some color on the share repurchases. Today, we are pleased to announce that our Board of Directors has authorized an increase to our share repurchase program, under which we may repurchase up to an additional $800 million of our common stock. Please note this authorization is in addition to the $200 million buyback the Board authorized last quarter to offset the dilutive impact of the Voyage AI acquisition, bringing the total authorization to $1 billion. This decision reflects our confidence in the long-term potential of our business and underscores our commitment to delivering value to our shareholders while maintaining a flexible capital structure. I would note that we did not repurchase any shares in Q1, as the CFO search process prevented us from initiating the repurchase program. It is our intention to begin repurchasing shares in Q2. Now, moving on to our four-year guidance, I'd like to provide some incremental comments on our expectations. First, as we discussed, we had a strong start to the year. and feel good about our ability to drive continued revenue and profitability growth, even with a more uncertain macroeconomic environment. We are raising our full-year revenue guidance by $10 million, which reflects the continued confidence in Atlas while incorporating some timing differences in our EA business. Second, our expectations for non-Atlas subscription revenue have not changed. We continue to expect it will be down in the high single digits for the year, though we will continue to expect non-ATLAS ALR will grow year over year. As a reminder, we expect an approximately $50 million headwind from multi-year license revenue in fiscal year 26, primarily impacting the second half of the year. Finally, we are raising our expectations for operating margin to 12 percent at the midpoint up from 10 percent in our initial fiscal year guidance. We remain committed to a balanced investment approach that supports our key long-term growth initiatives. As CFO, one of my key priorities will be working closely with leaders across the business to identify ways to both reallocate existing spend to higher ROI opportunities and be more disciplined about incremental spending. We are focused on running an efficient scalable business that supports growth in revenue and profitability to drive long-term shareholder value. Moving on to our Q2 guidance, a few things to keep in mind. First, I want to remind you that Q2 has three more days than Q1, which is a sequential tailwind for Q2 Atlas revenue. Second, we expect to see high single-digit year-over-year decline in the non-Atlas business after a stronger than expected Q1. And third, we expect operating margin will be lower than in Q1 as we have invested in targeted areas to drive growth. In addition, the expected sequential decline in non-Atlas revenue will be a headwind to profitability in Q2. With that context, I will now turn to our outlook for the second quarter in fiscal year 26. For the second quarter, we expect revenue to be in the range of $548 to $553 million. We expect non-GAAP income from operations to be in the range of $55 to $59 million, and non-GAAP net income per share to be in the range of 62 to 66 cents based on 87.5 million estimated diluted shares outstanding. For fiscal year 26, We now expect revenue to be in the range of $2.25 to $2.29 billion, an increase of $10 million from our prior guide. We are raising our non-GAAP income from operations expectations by $57 million and are now targeting a range of $267 to $287 million, and non-GAAP net income per share to be in the range of $2.94 to $3.12 based on 87.6 million estimated diluting shares outstanding. Note that the non-GAAP net income per share guidance for the second quarter and fiscal year 26 assumes a non-GAAP tax provision of approximately 20 percent. To summarize, MongoDB delivered strong first quarter results. We are pleased with our ability to drive growth across the business and increase our operating profitability expectations. We have a small share in one of the largest and fastest growing markets in all of software with a number of secular tailwinds at our back. We remain incredibly excited about the opportunity ahead and will continue to invest responsibly to drive long-term shareholder value. With that, Josh, we'd like to open it up for questions.

Thank you. As a reminder, to ask a question, please press star 1 1 on your telephone and wait for your name to be announced. To withdraw your question, please press star 1 1 again. Please limit yourself to one question and one follow-up. One moment for questions. Our first question comes from Sanjit Singh with Morgan Stanley. You may proceed.

Yeah, thank you for taking the question and congrats on the strong Q1 and really nice to see the Atlas growth accelerating on a day-suggested basis and on a reported basis as well. Dave, I had a question for you and then I had a question for Mike as well. Dave, to start, when we think about what's driving Atlas growth, can you frame it in terms of the type of applications that are being built? In your script, you sort of distinguished cloud-native distributed real-time today versus the AI apps for tomorrow. And so I'd just love to get a sense of the nature and style of applications that are being built on Mongo that's driving this accelerated growth?

Yes. So, Sanjay, thanks for the question. What I would say is that we still talk to customers who have very near needs for running their business, building new applications to drive operational efficiency, building new products and services through software to drive, to take advantage of new revenue opportunities, and to continue to drive more innovation in their business. I think what people find attractive about MongoDB is that you really can use it for a wide variety of use cases. You can support very transactional-intensive use cases. You can support more modern use cases, things like IoT, streaming, and so on and so forth, as well as being able to also support some of these more modern use cases like AI. And the fact that you can do this all on one platform where you don't have to stitch together multiple tools that the underlying architecture is designed to really help you model the real world to be able to handle complex, nested, and evolving data, to be able to scale elastically, to be able to run these applications on any cloud, across clouds or on-prem, just makes MongoDB a very attractive solution. And we feel really good about the fact that we add a lot of customers. So what it really shows is that, you know, Customers and developers are voting with their feet to really adopt MongoDB.

Awesome. And then Mike, for you, congratulations on the CFO role. I would love to get just your sense of the opportunity ahead from you. And mostly I want to get a sense of how you're thinking about, on a first principle basis, how you plan to manage and message the metrics and the numbers You're a longtime, highly experienced CFO. This is your seventh stint. But this is a consumption model, right, which has, like, more variable components. So I'd love to see how you're thinking about that as you take on the role from a growth perspective but also from an operational discipline perspective.

Yeah, so thank you for the question, Sanjay. It's actually a very interesting one. So I think the company does a wonderful job, actually, on the metrics that they give. know we had experience in a consumption business at my last role as well and going through all the data and meeting with the team in the uh in in the fire hose that has been my onboarding uh there we have a lot of data i think that the metrics that we talk to investors about are very relevant in terms of consumption in terms of customer growth um so at this point again it's the non-excuse it's just a fact eight days in i would say not a lot of change there I do think that we will spend a lot more time going forward on a couple things. One is just the capital structure, the cash flow generation of the business, as well as the operating margin improvements. And this will certainly change. I would also underline, hey, come in September to the .local event. That will give me at least another quarter under my belt, and we'll talk a little bit more about what you can expect from MongoDB going forward. Makes total sense. Congratulations again. Thank you.

Thank you. Our next question comes from Raymond Lynch with Barclays. You may proceed.

Hey, perfect. Thank you. I had two quick questions. One for Dave, one for Mike. Dave, if you look this week, we saw snowflake kind of move and make the move towards post grass. We saw snow. Databricks kind of doing something there. Can you kind of frame that? Because obviously like from the outset, it looks like, you know, you know, there's like a big embrace going on, but like maybe contrast and a little bit like, you know, where you fit in and where some of those moves could fit in. And that's my first question. And then for Mike, like, I know you have only had eight days, but when you did your due diligence, looking at the company and also looking at the strong performance on the profitability, like how do you think about this business? Because that's one of the things that, people would have kind of talked with the previous team about is the profitability level of this and if there's something inherent there or if there's something just that can be done about that. Thank you.

Thanks, Raimo. To your first question, I think the moves by both Databricks and Snowflake, I think validate one thing, that OLTP or the operational data store is the strategic high ground, especially for AI. That's where inference happens. Inference is the big market. That's where everyone wants to go. and you need to have an operational data store to do that. And I think the other thing it points out is building organically an OLTP store is really hard, especially when you need to meet the requirements of enterprise scale, availability, resiliency, and security. And both organizations had signaled that they were working on organic approaches. You know, Snowflake talked about Inastore, Databricks had talked about their own organic efforts, and it's clear that they couldn't make it happen. So this is not an easy task. The second point I'd make is that just because they're buying small Postgres companies, I think Neon, I would say, was in the vibe coding space, and I would say Crunchy Data is a small relational company based in South Carolina. I would say that it's not clear to me why the world needs a 15th or 16th Postgres derivative database. I think we'll find that out. I think there's also some noise about how Neon is 80% of its instances are provisioned via code. I should point out that nearly 80% of MongoDB instances on Atlas are provisioned via code. And so we do that to help our customers provision and scale clusters very, very quickly. And so the real advantage is architecture. And we believe that the fact that Postgres and other relational platforms are now adding JSON is a tacit admission that the core tabular architecture just doesn't get the job done in the world of AI. Developers need to be able to model the real world data, which is complex, messy, nested, which means it has highly interdependent relationships and is constantly evolving and changing. And then when you look at the fact that they've bolted on these capabilities, if you add a document size greater than two kilobytes, it's going to deliver a very poor performance. And so the superficial compatibility does not mean it's native, does not mean it's production grade, does not mean it's designed for enterprises. And so if the competition is now on who's going to compete for these complex AI workloads, we welcome that challenge because architecturally we think we have a huge advantage.

So, hey, Raymond, it's Mike. So thanks for the question. I would highlight kind of four areas when I did the diligence on MongoDB. And I can say in the first eight days, nothing has changed my mind on any of these. First of all, hey, there are few companies that are greater than $2 billion of revenue where their main business is growing 20% plus, the total business growing double digit with 70% plus gross margin. So stop there. That's a scale business that has a lot of leverage built in. So the four things I looked at is already had the scale from an international and from a product perspective, and the main business now is 72% growing very quickly. Number two is this is a business model that has leverage because you can bring additional revenue in. It's going to come through the gross margin line at high margins. That leaves a ton of room for investing in the business, but also candidly for driving more efficiency as well. And that was the third piece. When you look at it, and nothing against the company as it sits today, as we grow, I'm completely confident we can continue to invest in the business but become more efficient. And then the fourth part was, hey, it's really nice to come to a business that has a super clean balance sheet and a bunch of cash on there as well. That leaves a bunch of flexibility going forward. So all of that I looked at and said, wow, what a great opportunity. And then, of course, I looked at where you folks were valuing the business, and I said, wow, that's a really good opportunity.

Perfect. Very clear. Thank you.

Thank you. Our next question comes from Jason Ader with William Blair. You may proceed.

Yeah, thank you. Sorry to beat the Postgres horse here, Dave. But my question is, you know, a key part of the bull narrative is for Mongo has been that document databases would steadily take share from relational, and then Mongo would become the default general purpose database for modern apps. I guess my question is, does the rising popularity of Postgres among developers and the strong ecosystem it has, as we see from what Snowflake and Databricks did and what the cloud guys are doing, does that suggest that relational just may have greater long-term relevance than initially anticipated?

Yeah, Jason, thanks for the question. And I think I want to clarify some of these misconceptions that are out there. One is that this is a big market. It's $100 billion plus market, so there can be multiple winners. Second, the Postgres popularity is really a function of the consolidation of the SQL market. People are leaving Oracle, leaving SQL Server, leaving MySQL, and going to Postgres. I think the third thing that I should mention is that Postgres does have this veneer of being an open source, open standard, not owned by any one vendor. But there are literally every vendor, including the hyperscalers, have their own version of Postgres that build proprietary extensions and other capabilities that actually make it very difficult to go from one version of Postgres to another version of Postgres. With MongoDB, you can actually run any workload on any cloud, across clouds and on-prem, without changing a line of code. And last, I would say architecturally, we are far better optimized for this new world of complex, modern applications, especially in the world of AI. JSON was designed to really address the needs of this modern world, how data is very messy, how it's very interdependent, how it changes often, There's no predictability in the format. There's no uniformity on the structure. And MongoDB is designed to handle that world. And when relational databases start trying to mimic our features, what does that tell you? It tells you that their existing architecture is not designed for this world. Now, there's no question when the technology has been available for 40, 50 years, there's a large group of people who understand that technology. But we feel we're well-positioned. We have more work to do, but we feel well-positioned to be a winner in this next wave of applications that are being built and we feel confident about our position.

One quick follow-up to that, Dave. Thank you for that answer. Should we be thinking about then, I don't know, over the next five plus years or something that the two big winners in the database market in terms of architecture will be Postgres sort of for the relational crowd and Mongo for the non-relational crowd? Is that how we should be thinking about it? Is that how you're thinking about it?

Yeah, I would say, I definitely think that there will be multiple winners. This is not a zero-sum game. I also believe that, you know, the other point I want to clarify is a lot of people compare MongoDB to Postgres, and that's actually a false comparison. By us embedding, you know, keyword search, by us embedding a native vector search, by us embedding embedding models, you're really comparing MongoDB to Postgres, plus Elastic, plus Pinecone, plus something like Cohere. So the value for customers is that they don't have to stitch all these capabilities together. They get all these capabilities in a very elegant, natively built way that allows them to move fast. It's not a very complex architecture, and it's much more cost effective. But I do think there will be multiple winners. And for people who want to stay on relational, Postgres is a very viable option. but we think that we have a big opportunity in front of us.

Thank you.

Thank you. Our next question comes from Kash Rangan with Goldman Sachs. You may proceed.

Thank you very much, Dave. One for you and one for you, Mike. Congratulations on joining Mongo as CFO. Dave, can you give us a mark to market on where we are with some of the growth initiatives you undertook, such as Relational Migrator, the move up market, the reconstitution or the refocusing of the sales force towards higher value accounts. And I think you have discussed metrics such as the productivity superiority in moving up market. And if you could just not only give us a market to market, but how is that new push showing up in terms of incremental productivity metrics? Obviously, the customer lands have been quite good, but with respect to growth rate, It does not look like we're quite yet at that inflection point. Maybe if you could just give us a little bit more of your introspective analysis on that. And then, Mike, one for you. You talked about second-half dynamic with respect to, I believe it was the EA business. Can you expand upon that a little bit and what could go right versus that austere assumption? Because, after all, we didn't see upside in EA this particular quarter versus not your guidance but your previous guidance. Thank you so much.

Thanks, Cash. So let me start. So when we talked about the strategic initiatives, we really called out three things. One, R&D investments. Two, moving up market. And three, putting more focus on awareness and education. So on the R&D investments, I would tell you that we're already seeing returns on investment. We said we're going to double down on the core. We introduced MongoDB 8.0, which is the most performant release we've ever issued. And I will also point out that it's also had the fastest uptake of any major releases. Customers are adopting ADO two times faster than our last major release. We're also expanding our engineering efforts around AI and Voyage because that's a super exciting area for us. And we're also investing in product tooling for our own app modernization. And last but not least, we're bringing more senior talent to really complement the existing team so that we can really have a broader ambition. So that investment is paying handsomely. The move-up market is also going well because a part of our results are a function of the fact that we made that move starting in the last year, and we're starting to do bigger deals. We've signed some very, very large deals with some very, very large enterprises, and the productivity of that team has always been quite high. And I would say a complementary move is that our self-serve business is starting to acquire mid-market logos serving them more efficiently without ceding ground to anyone else. And that shows up, as you see, in our customer account this quarter. And then in terms of awareness and education, we are aggressively investing in a few areas. One, we're aggressively investing in the Bay Area. That's where the next-gen AI companies and the next-gen AI developers are highly concentrated. And we're starting to see some traction there. And we have some high-profile AI customers already on our platform and lots of other smaller customers. We're investing in attracting relational developers to learn more about MongoDB, so we're attending relational conferences, putting together more training and more skills for people to upskill their abilities and also providing certifications. And what we also find is a lot of the new Atlas registrants are actually new to MongoDB, so we're spending a lot of time making sure they're onboarded properly and taking full advantage of all our capabilities. And then we're all, you know, as part of the training, we're upskilling developers on modern databases, right? As I mentioned, certifications, self-paced courses and all that. And we also expanded our documentation to Mandarin, to Portuguese, to Korean and Japanese because MongoDB truly has a global business and there's developers all around the world who want to use MongoDB. And I think we're just getting started. There's more things we're doing that I just can't talk about right now around, especially on awareness and education. But the key point is there are some misconceptions about MongoDB that we know we need to address. and we're quite excited about the opportunity to do so.

So thank you, Cash, for the question. This is Mike, and for the kind words. So just for context, as we talked about in the prepared remarks, so for the full year, we remain competent in the business. We took Q1, we exceeded our expectations, and we largely rolled the beat from the Atlas business into the full year number. As it relates to non-Atlas and then specifically your question, we had a good quarter in the EA business. Some of that was timing. So we adjusted the Q2 through Q4 non-Atlas business to take that into account. As it relates to the $50 million multi-year headwind you talked about, that's largely due to the renewals and the timing of those renewals from fiscal 25. So we have maintained that same guidance. To the extent that it could be better than it may, then that would certainly be an upside. Keep in mind, though, that those are renewals based on when those customers come up, so it's not completely in our control. There may be upside, but at this point, we're still holding to the same guidance.

Super. Very granular. Thank you so much.

Thank you.

Thank you. Our next question comes from Brad Reback with Stiefel. You may proceed.

Great. Thanks very much. Dave, last quarter you talked about AI only being modestly incremental to revenue growth in 2026 here. Is that the same expectation 90 days later?

Yeah, so what I would say is the following. We see thousands of customers building thousands of apps on MongoDB, and that's growing quarter over quarter. We are seeing some high-profile, well-known AI companies. I mentioned Cursor on the call earlier. and there's a few other high-profile companies who are building on top of MongoDB, and obviously those businesses are really taking off. But what we see is that enterprises are still early in the adoption of AI. The barriers include there's a limited set of skills and experience with AI, trust with AI systems that are probabilistic, which is another way of saying the risk of hallucinations. And so we see obviously some early use cases around operating efficiency, chatbots, CodeGen, and domain-specific ISVs like Harvey, that customers are using. And we've already seen, as I mentioned on the call, LG U+, we have Swisscom, Novo Nordisk, Central Reach, or a bunch of customers I mentioned in the past who have already deployed our AI capabilities. But the real enduring value will come when people start building custom AI apps. And the point I want to make is that anyone can use an ISV to run their business, but that doesn't give them a competitive advantage because their competitors could use the same ISV What really gives them a competitive advantage is building custom solutions around using AI to transform their business, whether it's to seize new opportunities, to respond to new threats, to drive more operating efficiency. And when people start really learning about MongoDB, the document model can handle these complex data structures. We have best-in-class voyage embeddings to improve the accuracy of these results to help people get comfortable with using AI. And by integrating text search, you know, vector search and embeddings and operational data, that's a unique differential. It makes the developer's life easy, reduces cost and complexity. And so we feel, you know, we're well positioned for this, but it's still early. Most enterprises are still early in the adoption of AI.

Great. And then on the go-to-market side, any meaningful changes on the kind of upper market comp plan that we should be aware of?

No meaningful changes. We feel good about what's happening at the high end of the market, and we also feel good about our self-serve business being able to acquire customers more efficiently. So we feel like those motions are working.

Great. Thank you.

Thank you, Brad.

Thank you. Our next question comes from Brent Braceland with Piper Sandler. You may proceed.

Thank you. Good afternoon, Mike. Great to hear your voice again here. Welcome aboard. Dave, one of the challenges that we've had with the story here is that the Atlas business has been decelerating here, moderating growth for about three years. This was the first quarter where we actually saw Atlas growth re-accelerate. Pretty big step up here in the number of net new Atlas customers. Would you now say you feel like you've kind of bottomed relative to the growth profile of Atlas, and you're kind of now on a newer, more stable trajectory going forward. Just walk me through what looks like a meaningful reversal here in the Atlas business.

Yeah, so we're very proud of our results in Q1, and much to what Mike mentioned earlier, when you look across the landscape, there's not many companies who have a their core business growing at 26% year-over-year at our scale. Atlas is a very large business, and so there's not many companies who are growing at that rate. And we feel like what's on the horizon in terms of AI, I haven't talked about app modernization, where we can help customers more efficiently reduce the cost and significantly reduce the time to modernize legacy applications. That gives us easier access to a large market. And so those are also initiatives that we're spending a lot of time and investment on. And there's lots of customers that still need to run their business and continue to build applications that are core to their business strategy. So we feel good about our opportunity. Our guide is our guide. We feel good about the quarter and We also feel great about the fact that the customer ads were very strong this quarter, which shows that people are embracing MongoDB.

Thanks for that. And then, Mike, I know you're eight days in, fire holes here. Increased focus on margin improvement reads loud and clear. You did talk about kind of balance sheet. This company does have a lot of cash. I know you're putting a billion dollars of it to use to the buyback. Other uses of cash, do you see an opportunity to maybe get a little more aggressive on M&A, small tech tuck-ins to also maybe help accelerate the AI opportunity? Walk me through kind of use of cash. Thanks.

Sure. And thanks for the comments. Great to hear your voice as well. So on the buybacks, just to hit that, hey, we're super excited about the board expanding that up to a billion dollars, and we will be active as it relates to the buyback. For the rest of the cash, what I'd say is, hey, we feel really good about the organic growth story here. And that's the focus. To the extent that there are smaller tuck-ins or we could do roadmap accelerations and use some of it, not a lot of it, that's certainly up for debate as well. So it does give us that option. I would say we don't think we need to do M&A to achieve our targets, certainly. But to the extent that we think it can help, it is nice to have the available cash. Good to hear. Thank you.

Thank you. Our next question comes from Mattai Kidron with Oppenheimer. You may proceed.

Thanks. I appreciate it. Dave, I want to dig in a little bit into the high-end focus, the large enterprise. Is there any data you can provide, proof points, kind of under-the-surface data points that you're tracking internally about progress here? Anything about pipeline, number of Fortune 2000 logos. Help me think about the evolution here. And at what point do you think we'll be at full run right here on this group?

Well, I will tell you that I think we already have meaningful traction. I think we previously disclosed that 75% of the Fortune 100 are existing already MongoDB customers and 50% of the Fortune 500 are MongoDB customers. So that tells you that we already have meaningful traction. And what we realize is the biggest opportunity for us is to expand in those accounts. I just recently had the CIO of one of the largest healthcare companies in the world in our office. I just met with the senior leadership team from one of the largest financial services companies here in New York. And then I met another team from another financial services company in New York. And they're bringing us in saying, we want to have a more strategic relationship with you. So I feel like the motion is working. We're doing larger deals. And the productivity of the sales team focused on those accounts is materially higher than the typical sales rep. So we feel like it's a motion that we will invest on for the long term. And I think the results will obviously speak for themselves, but we feel really good about our move up market. And I also want to point out that our self-serve motion is a nice complement to that move because it allows us to acquire you know, lower end customers, mid-market customers much more efficiently. So we're not like ceding ground to anyone in that segment of the market.

Yeah, that's great to see. And Mike, for you, first of all, congratulations. I'm looking forward to working with you. A couple of small ones. First of all, you talked about the slord and plant headcount addition in the quarter. Can you tell us in what areas and is this going to be an issue down the road in that you're kind of, you're a little bit behind on headcount additions? And also you guys for the year, you raised it by 10 million. The beat was greater. Can you tell us when and where are you a little bit more conservative than on the reminder of the year and what part of your business?

Sure. So let's take the headcount first. So it was really broad based across the whole team in terms of slower headcount additions. There was nothing that we didn't pull back or say, don't hire. It just takes longer. So nothing there. We also don't have any concerns around does that mean lower, for instance, sales capacity largely due to what Dave talked about on the go-to-market. So do we think it goes forward? It certainly is a part of us, I would say, moderating our OPEX expectations for the rest of the year, hence the increased 200 basis points. So that's the headcount piece. On the beat and raise, so we did beat by 20 million in the quarter. As we talked about, we largely rolled the Atlas beat into the full year number and left the rest of the year where we were. We felt good about what we guided to after Q4. Hey, there's a lot of uncertainty as it relates to the world, tariffs, the economic situation, and everything else. So we think it's prudent to leave that guide there. We did come down by 10 million in the non-Atlas business because that was largely timing. And as we said, We're still holding to the EA forecast that we did on a year-over-year basis. Now we'll see where that goes. It's also the hardest piece of the business to forecast because of those larger deals. So we thought that that was the prudent way to guide the year.

I appreciate it. Thank you. Thank you.

Thank you. Our next question comes from Andrew Nowinski with Wells Fargo. You may proceed.

Great, thank you. Maybe I just wanted to follow up on the Atlas guidance. I know you're saying that, you know, consumption was in line with your expectations, but can you just provide any more color on sort of the mechanics of growth in that consumption segment? Because it would seem that the outperformance in Q1 would set you on a higher trajectory for the full year, you know, due to the fact that it is a consumption model, unless there's some sort of drastic change in the, you know, global economy that would change a customer's consumption patterns?

Sure. So, Andrew, it's Mike. So, thanks for the question. So, if you take a step back, and that's what we saw in Q1, we talked about the monthly consumption patterns there. We did a little bit better early in the quarter, and April was a little bit soft. The dynamic that you just talked about is exactly what's baked into the guidance for the rest of the year. We continue to expect Atlas growth to be strong as we go through the year. We are also cognizant of April is a little bit soft, may pop back. We'd like to see a couple more months of that going into the year. Hopefully we feel more confident as we go into the second half. But at this point, given all the economic uncertainty, we certainly hope there's upside, but we'd like to get through another quarter.

Understood. And Mike, thank you. It's great to reconnect again from our days at NetApp. My second question is really more on a higher level. I understand the performance and scalability advantages of MongoDB over or I should say a document database over a relational database, but have you maybe thought about or considered or heard any sort of feedback from customers as to whether MQL might be simply maybe more difficult for a developer to use versus SQL and maybe that's why you're seeing sort of this increase in interest in Postgres? Because it's certainly not a better performing database. I think everyone knows that, but maybe it's just a query language issue.

So, again, thanks for the question. I just want to, again, say we're going after a big market. I think the Postgres popularity is a function of people basically leaving other relational platforms, in particular Oracle, SQL Server, and MySQL. So that's why you're seeing developers kind of move to Postgres. But I would tell you that Postgres is a tabular database, much like all relational databases. So then the question you have to ask yourself is, they announced support for JSON. Why did they do that? And they did that because it was tacit admission that that architecture just doesn't get the job done in a world that has to deal with data in the real world. Data in the real world is complex. data in the real world has a lot of dependencies. Like, I'll give you some examples. Like, you know, if you want to model the message that has attachments or reactions or part of a threaded conversation, how do you do that in a structured table? If you want to deal with, you know, adding new fields or, you know, new values and all that, how do you, you know, for example, if you have a user who has suddenly multiple phone numbers, how do you model that quickly? How do you deal with nested structures, right, where... A customer record could include past orders, each with their own line items and order history. How do you do that? It's much more difficult where you can model that so much more easily in MongoDB. How do you deal with messy, inconsistent data that there's no uniformity to? we recognize that some people who don't know MongoDB may not really understand all these advantages, which is why we're putting more emphasis on awareness and education. But fundamentally, if you see why these relational databases are adding JSON support, it is acknowledgement that their existing architecture cannot, you know, you know, evolve to natively evolve to serve these new needs. And that's why we think we're well positioned because MongoDB is a native JSON database. It's a document database and it's distributed. It has designed to scale and the latest release is the most performed release. We're even more excited about 8.1 that's coming out soon. We acquired Voyage. That's going to be natively part of the platform. We're going to, you know, later this month, we'll enable people to seamlessly generate embeddings from data sitting inside MongoDB, and that will be in private preview. So that's within four months of the acquisition. So we're moving fast, we're innovating quickly, and that doesn't even mention, you know, our core vector search engine as well as our keyword search engine. So when you put all these things together, it becomes a very compelling platform, but we recognize that some customers and some users just don't understand all these things, and that's what we're focused on addressing.

That makes sense. Thank you so much.

Thank you. Our next question goes from Mike psychos with Needham. You may proceed.

Hey guys, thanks for taking the questions here. Um, Mike, just to come back to the, the monthly trends that you guys saw on the Atlas consumption side. And I really, really appreciate all the color there. Um, if you're talking about this rebound that we saw in may, And I know we don't see like a consumption growth year on year usage growth year on year to the detail that you do, but is that year on year growth and consumption in May, um, back to the levels that we saw in February or March, or is it still lagging based on that April softness that you had described?

So it's much more consistent with what we saw in, in February and in March, April was a little bit softer. And then, as we said, it was a healthy rebound in May.

Great. Thanks for that. And then, Dave, just one for you. I know that we have some of these go-to-market changes. I'm looking at the new logos that you added this quarter specifically, and I mean, you guys have been, you have been a native JSON database. You have been that NoSQL vendor. Can you help me think about, like, why are we seeing this meaningful bump in the new logos acquired this quarter specifically? It really looks like the self-serve was taking off, but just interested in what you're seeing on that front. Thank you.

Yeah, I mean, you have to remember, our self-serve business was a new skill that we developed, frankly, organically here. And then actually May Petrie, who's been promoted to CMO of the company, was the one who led our self-serve business since early 2022. She and her team have really done a great job of really growing that business being much more sophisticated in running experiments, how to attract the right level of customers, and that is showing up in the numbers. And as we move up market, we want to take advantage of that self-serve capability to be able to acquire more customers in the mid-market, and so that's something that we're going to do. And so we feel really good about the combination of our direct sales force as well as our self-serve business in terms of how we approach the market. And... And I would say that when we are able to get in front of customers and explain our differentiation, customers understand and want to use MongoDB. Our biggest challenge is making sure people really understand the differentiation and don't have certain misconceptions of what we do or what others do.

Great. Congrats on the demonstrated success on that front. Thank you.

Thank you.

Thanks, Mike.

Thank you. I would now like to turn the call back over to David Itacheria for any closing remarks.

Well, thank you for joining our call. First of all, I would like to thank Mike. Eight days in, it's obviously, you know, preparing for an earnings call is hard work, and to do it in eight days is pretty impressive. So I really appreciate everything he's done to prepare for the call today. You know, again, we had a strong quarter with a record total customer net additions. We're raising our revenue and operating margin guidance for the full year. We're moving forward with a billion-dollar total share repurchase program reflecting our confidence in the business and our commitment to delivering value to shareholders. And we're more excited than ever about our long-term outlook, particularly our position to fundamentally address the needs of workloads in both today's era and tomorrow's era driven by AI. So thank you very much for the call, and we'll talk to you soon.

Thank you. This concludes the conference. Thank you for your participation. You may now disconnect.