Back
Earnings Call Transcripts

MongoDB, Inc.

MDB
Quarters2 Quarters
ContentQ&A Sections
SourceEarnings Conference Call
Quarter 1

Q4 2026 Earnings Call — March 2, 2026

Management: Thank you.

At this time, we'll conduct a question and answer session.

Analyst Raymond Linshaw (Barclays): Hey, thank you. Congrats, great fourth quarter. Two quick questions. One for you, CJ. At your big event in January in San Francisco, what were your impressions about developer buy-in? Part of the reason for doing it is to increase mind-share again. Share a little bit your experiences there. And then one for Mike. On EA, next year had a bigger cohort, and this year, I'm just wondering if the strength in the second half this year, was that earlier renewals for next year, or is the cohort still in place? Thank you.

Executive CJ: Thank you, Remo. Appreciate it. So January 15th event, DOT Local San Francisco, I would consider a great success. And I would put that in two buckets. Number one, we exceeded, even though it was a weekday, many, many founders, builders, who came to the event and there was a long line outside for people to get into the conference. That gave me really, really good feeling that we invested in the right area. Number two, when we looked at the attendees, Remo, I would say compared to other typical DOT local events where people who are already customers or builders of MongoDB. Here, around 70% had not used MongoDB. And that's what gave me a lot of conviction that it was a successful event where we are increasing the mindshare of the builders in the San Francisco Bay Area where a lot of AI-native companies are being built. The last thing that I'll touch on is that because of the success of that event, and continue to make sure that we are on top of mind for all these AI-native companies, whether they are in security, whether they are in fintech, whether they are in domain-specific AI, we are going to repeat .local in San Francisco again in August this year, which we have not done before based on the success.

Executive Mike: Thank you, CJ. Remo, thanks for the question. So on EA, a couple things. So we're super excited about the year we have, fiscal 26th. was a very strong year, and especially Q4, not only in the run rate business, but obviously all the multi-year deals. So, hey, it's a big business, thankfully. There's always some puts and takes in terms of renewals. I would say there's no material change to the cadence of early renewals. And keep in mind that even if there is one, you won't see it in revenue until that deal comes up. So you shouldn't see any major impact in cohorts next year.

Analyst Matt Martino (Goldman Sachs): Yeah, thanks for taking the questions. CJ, maybe to start with you, you noted the transition for Cedric and Paul has been in the works for some time. Given that visibility, can you provide more color on the current status of the CRO search? And specifically, what are the primary attributes you're looking for in a successor that led you to announce Erica's appointment today while the search for a new revenue lead remains ongoing?

Executive CJ: Absolutely. So, Matt, here is how I would describe it. Personally, being here, as you have seen that I've spent a lot of time with not only our customers, but with our go-to-market team. So we are in the final stages, but we want to make sure that we get an excellent candidate for our chief revenue officer. Erica's focus will be as a chief customer officer to ensure that customers who are purchase or decide to use MongoDB platform, they get to value by providing all the post sales support functions, whether it's technical success, technical support, many other things like professional services. So one, Erica is going to focus on customers who have already bought MongoDB or expanding with MongoDB, how do they get to value and how do they get to success. In terms of the CRO search, Paul is staying fully through Q1 and help us transition through Q2.

And from the attributes perspective, I want somebody who is very focused on high end of the enterprise, understands how things work at MongoDB from a mainstream perspective, but also working with the management team as we expand into both the AI natives as well as enterprises who are building more mission-critical workloads on MongoDB, including AI. So that's the mix, I would say, is somebody who is strategic, who understands consumption-based models on how MongoDB really operates, of course, our enterprise advanced business and has relationships into the high end of the market where we are getting significant traction besides the AI-native companies, which is Harley.

Analyst: Okay, very clear. And Mike, maybe for you, just a couple of major EA deals were announced this quarter. CJ talked about the renewed importance of on-prem. I guess under that backdrop, should investors be recalibrating expectations around growth for the EA business as we look out over the next couple of years?

Executive Mike: Thank you. Yeah, thanks for the question, Matt. So as we talked about, so two things I think of importance in the prepared remarks. One was CJ walked through some very large deals. As you look especially at regulated industries, governments, it is a very important product that we have and those are some of the largest customers at MongoDB. In addition, we're starting to see more of the bundle deals. The on-prem piece is a huge part of it. So what I would say is, yes, it will continue to be of importance. We are actually investing in EA to bring it to parity to Atlas. So certainly our expectation and hope is that we continue to grow that and can even accelerate it in the future. Thank you both.

Executive CJ: And Matt, I would say in speaking to customers, because this conviction is over a large set of very important customers, there is definitely the trend that I'm speaking from our customers is number one, that because of variety of issues related to also AI, that for mission-critical application, there is this trend I'm seeing where they do want to keep that critical data estates on-prem. And this is not just only in financial services. We are seeing that in healthcare and other verticals like government. But when I was in Europe and even in Asia, I'm also seeing that that there is a preference for those industries to also use MongoDB potentially with EA and only certain workloads in the cloud. So this will play out, and all we wanted to outline in today's call is to say this is strategically very important, as in the product line for our customers, and we need to invest in it because it is strategically very important.

Analyst Jason Nader (William Blair): Thank you, guys. For CJ, my main question is, how is your product and go-to-market strategy changing, if at all, ahead of the growing reality that agents are going to be the things that are spinning up most databases and not humans in the future?

Executive CJ: I would say, Jason, I have a very simple philosophy here. And the philosophy also was validated by one of the AI-native companies that has completely built on MongoDB. They had many choices in many clouds, and they chose MongoDB. And my initial intuition was the same as you outlined, is that MongoDB's success over the last many years since the company was founded in 2007 was that builders or developers love MongoDB. And if that's the premise, there was a lot of work done in the product to ensure that it's a very natural way, flexible way, while keeping the business agile, as in the database agile, so that it can move with the business. We want to do the exactly same thing for agents, agents also need to love MongoDB. That requires to ensure that we have all the right integration with the right places, whether it's NCP or whether we are looking at making sure that our APIs in how you manage, how we auto-scale, how we auto-perform during the peaks and valleys, all of that truly needs to be autonomous and driven by machines. And that requires absolutely the focus from the engineering team that how would machines look at this if they want to provision an additional node or if they want to manage cluster because of resiliency across multiple clouds. So that will be the North Star for us, that our agents will love MongoDB as much as today human developers love MongoDB.

Analyst: Okay, great. And then just a quick follow-up on that. Is that going to come in a future release of the database, or how should we be thinking about sort of the deliverables on that vision, C.J.?

Executive CJ: Jason, we do have ambitious roadmap, of course. Today, we are already leveraged by some of the AI native companies, and some of them I outlined this time and also last time, and we are learning a lot from them. So we have ambitious roadmap in terms of truly machine-friendly APIs or making sure that our protocol integration across a variety of protocols that machines demand, and how do we auto-scale, auto-shard. All of that will be throughout this coming year. And what we are going to do is at our DOT local conferences throughout this year, we will use that as an opportunity to announce new innovations that will show you that machines should also love MongoDB. So it will be throughout this year.

Analyst Ryan McWilliams (Wells Fargo): Thanks for the question. DJ, great to hear about Anthropic as a customer at the MDB local event. Love to hear how you think about the opportunity for Mongo to grow within large AI natives from here. And there's also mention at the event that agentic workflows require heavier storage and memory requirements. We'd love to hear why you think MDB architecturally is best suited for these growing types of AI use cases. Thanks.

Executive CJ: Absolutely. Ryan, you know, one of the things I would say is Mike and I look at the entire cohort, AI natives, frontier model companies, others, many of them choose MongoDB for performance scale, security, and other things. And I would say that the good news here from my standpoint is that we are not concentrated in any one customer when it comes to AI native cohort. So that's number one. And as they scale, we will scale with them. But we are not concentrated, even when I look at the growth as a percent of total, we were not concentrated. The thing that I'm seeing, Ryan, very specifically is that people are making initially database decisions in these AI-native companies without realizing that they will run into scale issues or potentially there was, you know, one of the choices that people could have gone with as an AI native company's founders had a massive security concern over the weekend where a couple of governments blocked them from being used.

So what I find is that truly enterprise class database that can scale, and when I say scale specifically, As for these AI-native companies, as their weekly active users or monthly active users continue to grow, like the example we had with Emergent or 11 Labs and so on, they find that MongoDB scales better with them, write performance as well as query performance really matters, and us being a native JSON with search, vector search and embeddings in one rather than multiple moving pieces. If I have to just simplify that, that is the strength because it's an integrated platform that scales both for read and writes that as you scale your AI-native company, they can rely that MongoDB will scale with them.

Analyst: Excellent. And then a follow-up for Mike. The Atlas seasonality in the fourth quarter seemed a bit lighter than typical. Were there any holiday impacts to the fourth quarter for Atlas revenue? or any other one-time items in the quarter besides the Atlas and EA bundling? Thanks.

Executive Mike: Yeah, thanks, Ryan. So looking back at Q4, the holiday seasonality played out largely as we expected. There were really no surprises or deviations from the historical trends, so it largely played out as we expected.

Analyst: Great. Thanks, Mike. Appreciate it, guys.

Executive: Yep. Thank you. We'll move on to our next question.

Analyst Carl Kersted (UBS): Oh, thank you, Mike. Let's stick to Atlas in the fourth quarter. A couple of questions. One, was the two-point beat roughly the framework you would advise the street to think about going forward? And then secondly, if you could just perhaps describe the bundling impact that, as you said, nicked a point off of Atlas, just maybe you could explain why that happened and were you anticipating that?

Executive Mike: Sure. So, all right, let's take a step back, Carl, on Atlas. So Q4 played out largely as we expected. As Ryan's question was, there were really no big surprises during the holiday season. We feel good about Q4 with 29% growth again with the bundle thing. I'll talk about that in a second. It would have been a little bit higher. As Atlas has gotten bigger, we are seeing less variability in the business. And in addition, we're getting better every day at forecasting the Atlas business. So from that perspective, the size as well as customer cohorts don't make as much of a difference in variability has helped. So on the bundling thing, so entering Q4, we certainly have our forecast as it relates to how we think Atlas will do. We always do bundle deals in a quarter, absolutely. This was a little unique in that we had one large transaction that once it closed, and thank goodness, again, it's a really good thing that it did, we had to attribute more of that revenue to EA versus Atlas, and that took a little bit off the growth rate. We did not expect that entering the quarter. So we typically won't walk through those kind of details because we always do bundled deals. This was an exceptionally large transaction, Carl, that did move the needle.

Analyst: Okay, that's helpful. And then maybe, Mike, as a quick follow-up, you mentioned you reiterated the medium-term guidance that you gave at the Investor Day. Maybe I missed it. I didn't hear the reiteration of the high teens total revenue growth. Is that still on the table, just to be crystal clear?

Executive Mike: Thank you for asking the question. Yes, we have not backed off on that total revenue growth from September. Sorry we missed it.

Analyst: That's all right. Thanks, Mike.

Executive: Thank you. One moment for our next question.

Analyst: Hey, guys. Michael, I want to follow up on the last questions here, mainly around EA. Clearly, you had a very strong fourth quarter here with two very large deals and also the bundle that you mentioned that weighed a little bit more towards EA rather than Atlas. I guess I'm trying to think about your guidance for fiscal 27. It seems like you have a lot of momentum there. You're closing some feature gaps. I'm kind of wondering why low mid is still the target for 27, why we hold this momentum in the fourth quarter and in the bundling and the feature parity you hope to achieve. That number is not higher.

Executive Mike: So thank you for the question. So we did have a very strong year in EA and Q4 especially. As we look out to the rest of the year, keep in mind that the product enhancements in bringing EA to parity with Atlas will occur throughout fiscal 27. So we are excited about that. And there was an earlier question about the cohorts. Keep in mind, it is a large business. There's lots of moving parts here. The biggest variability to the business is not the cohorts. It's what ends up closing as a multi-year deal versus a one-year deal. That still is difficult to forecast. And as we have said repeatedly, and we'll continue to say it, we will always bake in more upsides and downsides in that number. We sure hope to do better than that, but we don't want a negative surprise because a deal does not close on a multi-year basis, and that has such a big swing factor. So we feel great about the business. We're going to continue, as CJ talked about, a lot of big customers are asking about it. It's a key part of our portfolio, and we certainly hope to do better.

Analyst: Fair enough. And then maybe as a follow-up, just for both of you with the changes in the leadership on the go-to-market side and the CRO and the field, I guess to you, Mike, A, is there any more level of conservatism built in your guide because of this transition? And B, to you, CJ, year-end, any changes to comm structure that you're thinking about also in light of who you're looking for as far as the CRO is concerned?

Executive Mike: Yeah, so I'll answer it first. So when we do guidance, we obviously take into account a lot of things, the economy, all kinds of different things. So we have tried to bake everything in. It certainly, while it adds a level of uncertainty, I want to underline what CJ said in his prepared remarks. We've been working on this for a while. We feel very good about the team that's in place, and we don't expect any material disruptions. But certainly, that is a factor that we took into account when we did guidance.

Executive CJ: Itai, what I would tell you is that personally, after joining MongoDB, I have spent a disproportionate amount of my time with our go-to-market teams to really understand what is working really well and, of course, where we can improve. And I would say that the bench we have, so our leaders for America, our leaders for Europe, Middle East, and Africa, as well as our leader for now, APJ, I have very high confidence in them as we go through this transition. And these are the folks that really, really executed very well in fiscal 26 when you look at the regional performance, and I am really optimistic about their ability to execute as we move forward. In terms of, you know, overall go-to-market, how, you know, sellers are motivated, what we are looking for in the candidate to work on the main street with all these sellers and serve our customers, what I said to Matt is just remains the same, that no changes. We want disruption to be minimum. And with these three theater leads who exceeded even that number in Q4 greatly from a net new business perspective, I have confidence in them.

Analyst Alex Zulkin (Wolf Research): Hey, guys. Thanks for taking the question. CJ, maybe first for you, given some of the increasing inflection points that we're seeing in kind of the agentic coding space and autonomous coding that's happening, has that in any way changed the dynamic of how fast or how quickly you think that the enterprise modernization could start occurring? And then maybe just a quick follow-up for Mike to the point about the increased, maybe some of the surprising bundling, particularly with a large deal in the quarter. Is there maybe a little bit less visibility on specifically the Atlas Guide for both Q1 and the full year, given that increased potential for variability around bundling?

Executive CJ: Yeah. So, Alex, I'll touch on the first one. What I would like to say, so I was talking to a large financial institution in the UK, and the head of transformation, she told me that, hey, CJ, I have 50% of my real estate that I want to modernize. I know that some of the AI tools can get me to some level, but I really, really need to your help and your team's help to make sure that for this mission-critical applications, we take help from MongoDB to help us land once you prove this out for the first workload, a very critical workload that is moving to MongoDB. The same thing happened, Alex, with a large customer in Spain when I was there a couple of weeks ago. individual said, hey, we are relying on MongoDB as we are modernizing. This is extremely critical workload.

Once you do that, we are going to open up the aperture, and I know that AI will help us modernize, but we still need your help because the destination we want is absolutely MongoDB. So what I'm seeing is the feedback is the modernization and the need for modernization is still very much relevant in the high end of the enterprise, whether it's a healthcare company, financial services, or even government for that matter, or healthcare. Number two, they know that AI tools can help you to some extent, but they definitely want to get there on a modern database to get AI ready where they want help from MongoDB to be on MongoDB. And then the last thing I would say is that even with some of the use cases, they try it and they're like, hey, sometimes this is too hard to assure the reliability, security, and all of those things for the application we built. So I consider this as an opportunity in early stages, and this is definitely a top-down work that we have to do as MongoDB with the CTOs ahead of transformation, but the opportunity still exists and it's massive.

Executive Mike: Hey, Alex, thanks for the question. It's something that we will certainly watch. What I reiterate is, we always do bundle deals. It's part of what we do. Q4 was unique, given the size of that. I'd love to sit here and tell you that there's a whole bunch of those that we'll do every year. I do think right now it's unique. We'll watch it. We get better and better at forecasting the Atlas number every quarter. So at this point, we don't think it adds variability, but it's something we'll watch going forward.

Analyst Tyler Radke: Yeah, thank you for taking the question. Just going back to the EA and Atlas bundling, I guess I'm wondering, were these existing workloads that moved from Atlas to EA, or was it sort of plans for new workloads just a higher bias on EA? And just curious, why do you think that customer in particular chose to do more on EA as opposed to Atlas?

Executive Mike: So it's always going to be customer specific, Tyler. And a lot of these transactions will have renewal as well as upsell also. So it's very specific to the customer. And it really depends on their internal plans as it relates to how they want to use MongoDB going forward. So there's no pattern there. It's very specific.

Executive CJ: Yep. And Tyler, what I would say is that with this specific customer is that they have in the past moved some of their EA workloads to Atlas. Some of their Atlas workloads are growing incredibly well, and they want to continue to do that. and they are currently also getting ready for some of their workloads, AI-ready, where they are using vector search and embeddings in the future. So it is a kind of classic case of truly hybrid infrastructure on how they are dealing with their core product strategy, and some is built on EA and some is on Atlas. And from my standpoint, when we look at the numbers and the transaction, which was meaningful, as Mike said, very meaningful, is that what we also saw was the expansion because this customer, besides making a long-term commitment, continues to grow their data estate with MongoDB.

Analyst Tyler Radke: Great. Thank you. And CJ, a follow-up on the go-to-market changes. Clearly, your background at ServiceNow has one of the more successful partner ecosystems out there. I think on the database side, particularly for Mongo, the partner ecosystem, I think, has been tried, but certainly is not nearly as robust. And given that being more of a focus on some of the new go-to-market leaders bringing in, can you just help us understand maybe some of the challenges with the prior approach that didn't lead out to as robust of a partner ecosystem and what makes you and gives you the confidence that this approach is going to be successful?

Executive CJ: Yes, Tyler, absolutely. And I have been told what you just outlined. So I would put this in three buckets, Tyler. First bucket, which is super important, is our hyperscaler relationship and how we work with them. And as you know that we work with them very closely because when we win, they win, whether we are running on GCP or AWS or Azure or others, okay? So one bucket is just continue to still stay focused on hyperscaler. And in today's world, the multi-cloud resiliency, whether it's on-prem and cloud or between multiple public cloud, which is an advantage we have, it is proving out more and more important between the outages that happened last year with some of the hyperscalers and the geopolitical issues that we are seeing being played out. So that's number one. Number two, system integrators, which is where we scale at my previous company. That is definitely, when you think about the modernization and the real estate on modernization to move to MongoDB, we could definitely benefit by focusing on two or three of them to start with. And that is something that our teams are saying we do need help as we think about this two or three system integrators.

And make no mistake, the third bucket is also equally important is this AI-native ecosystem. There are framework providers, there are other providers like LLM providers, and what can we do with them and truly create partnerships that really matter? Those are the three buckets, and that will allow us to scale for a long time. So hyperscalers, a few system integrators who wants to lean in on the modernization, and the AI ecosystem where we really need to make strong technology friends is how I look about it, and I think it is extremely essential to do that, and this is the inflection point.

Analyst Sanjit Singh (Morgan Stanley): Great. Thank you for squeezing me in before the last question. So, CJ, I wanted to just get your latest thoughts on a couple of topics. Given that, you know, the business has been, you know, accelerating, execution has been improving the past several quarters, as we look forward, do we start to need to see like the kind of AI part of the story start to play a bigger role in terms of the growth equation? You guys have a number of AI customers as sort of we discussed at this call, but in terms of contributing growth, does that become more important as we think about potential upside to this guidance that you laid out? Kind of feel like over the last couple of weeks, we've seen a step up in terms of agentic momentum, not necessarily in the enterprise, still feels kind of consumer personal productivity, but just wanted to gut check your thoughts on the importance of the AI app story coming to fruition maybe a little bit earlier than you maybe anticipate.

Executive CJ: Yeah, I would tell you it's not if, but when, okay? So right now, we do consider, I mean, Sanjit, you know, one of the advantages that I have in speaking to all these customers, I ask them that simple question, where are you on your agentic workloads? And I'm talking about Fortune 500, okay? or big retail companies, healthcare companies, pick one, and ask them, where are you on agentic workloads and are they really scaling? And the answer is still not yet. Yes, they have done a few productivity types of apps internally, but nothing of scale that is customer-facing, even including with a large retailer on agentic commerce and so on. So my first thing is, one day, it is going to hit in a positive way where you will have agents making a meaningful difference to the growth of our customers for either new product lines or existing product lines. We are not seeing that today in the large enterprises across pretty much most of the verticals that we speak to because as you know, MongoDB is across every vertical. So my simple answer is, it will be someday. Not seeing that yet and don't want to predict it because it was supposed to be the 2025 was supposed to be that year. And what we saw in 2025, it was only mainly around coding and some vertical specific AI, but nothing meaningful in the enterprises.

Executive Mike: And just as a follow-up, and maybe, Mike, you can hit on this. It sounds like Atlas consumption more or less came in line with your expectations controlling for this large deal. You mentioned this potentially lower visibility in the second half. And I wanted to assess that comment in context of how the sort of calendar year 25, fiscal year 26 applications and workloads, how are they ramping relative to your expectations? Maybe if we look at the first half of last year and those applications ramping into this year, are you satisfied with the quality of that growth in that cohort of applications?

Executive Mike: Yeah, thanks for the question. So I think a couple questions in there. One is, yes, Q4 largely came in as we expected, except for that small thing that we talked about. There were really no abnormal things in Q4, which is great. On the comment about the second half, that's just more of a general macro comment, Sanjit, in that it is a consumption business. While visibility is always a little bit better earlier, we're also cognizant of, hey, it's harder to forecast the back half of the year. That does not tie directly to any concern around the workloads that we've signed in the last couple years. And, yes, those continue to perform as expected. As we've talked about, the strength that we've seen is really in the larger customers, especially in the U.S. and Europe. So all that is going as expected. That second half was more of a general comment, not specific to any set of workloads that were signed in the past.

Executive: Thank you very much. This concludes the question and answer session. I'll now turn it back to management for closing remarks.

Management: Thank you, Operator. In summary, we delivered an exceptional fourth quarter highlighted by strong Atlas and non-Atlas growth, robust customer additions, and operating margin outperformance. We are issuing strong guidance for Q1.

Quarter 2

Q3 2026 Earnings Call — December 1, 2025

Analyst Sanjit Singh (Morgan Stanley): Thank you for taking the questions. Fiscal year 26 is turning out to be quite the year for MongoDB, so congrats to the team all around. CJ, I wanted to start with you since this is your first earnings call. I heard you loud and clear in terms of what the goal is here to make MongoDB a foundational data platform for the AI era. In terms of making that happen in your kind of first 45 days on the job, maybe even less than that, are there some initial things that you're looking at, some kind of things that might fit in the sort of quicker wind bucket, and then longer term, what is, you know, what are some of the changes you think that the company can make or evolve to, to get to that, to get to that, to see your place in that sort of AI era?

Executive CJ Desai (CEO): Thank you, Sanjit. Here is, you know, this is my day 28 on the job, and I have been speaking to customers as well as our innovation team, including our Voyage AI team as well as our core database teams. The first thing I would say is the opportunity for MongoDB to be that data platform for AI workloads is very real because you need real-time operational data, you need the right context, you need to make sure that you are keeping up to date between the proprietary data of the company as in the enterprise, as well as the LLM learnings that the LLM model brings to the table. And most importantly, when I think about all of that combined together, MongoDB has all the elements needed to be the right foundational platform for AI workloads.

In speaking to customers, it is still early. There are various co-pilots when it comes to productivity types of applications that are happening inside of an organization, whether it's a bank or a healthcare organization or a manufacturing organization. But what I have not seen is truly AI agents running in production that fundamentally transform the business or serve customers better. There are many, many pilots still going on. When I contrast that with the AI native companies, and there is a really good, fast growth at scale AI native company that currently switched from Postgres to MongoDB because Postgres could not just scale. There is another AI company that highlighted that is using our embeddings as well as our vector database besides our operational platform. So when I combine all this together, Sanjit, what I see is as truly skilled agentic platforms where you can have enterprises creating agents that transform their business, MongoDB has a very important role to play.

And from a Low-hanging fruit standpoint, I would argue that our embedding model and re-ranking model is something that customers can start with today. Then they can move on to our vector database and use us for also real-time operational store. So that's how I'm thinking, and some of my initial customers' conversations have validated that theory.

Analyst Sanjit Singh (Morgan Stanley): Understood. I know it's early, so great to get out of that perspective. And then one follow-up for me, it's sort of a mark-to-market question. The calendar year 24, fiscal year 25 workload sort of improved in quality versus the prior year. I just want to get a sense of your sort of view on how the calendar year 25 workloads are shaping up as they will unlikely be a factor in terms of thinking about growth next year. So in terms of the quality of the workloads this year, can you give us a sense of the quality of those workloads?

Executive Mike Gordon (CFO): Hey, Sandeet, it's Mike. So what we'll say there is, as we said during the prepared remarks, and we saw this in Q2 as well, what we're really seeing is strength in the larger customers. It's not only from new workloads, but it's from the existing workloads. We don't want to bifurcate between which calendar year those were added. What we'd say is that we continue to see growth in the larger customers. They are growing longer and they're getting bigger and growing for longer, which is great, and we're seeing that across both the United States and then broad-based in EMEA as well. And, hey, as Atlas gets bigger and bigger, all of those kind of munch together because they're expanding, they're adding. So what we'll do is we'll focus on the growth in our larger customers, especially in the U.S. and EMEA, without going into each year.

Analyst Sanjit Singh (Morgan Stanley): Understood. Thanks, Mike. Hope that helps. Thank you.

Analyst Matt Martino (Goldman Sachs): Hey, thanks for taking my questions and nice to see another quarter of acceleration. CJ, I appreciate you're only a few weeks in, but I'd be curious to hear what customers are telling you is top of mind for MongoDB. You know, what are the repeated themes in customer conversations as you take a fresh lens to the business?

Executive CJ Desai (CEO): Absolutely, Matt. Great to hear from you. First thing I would say is that the modernization effort, whether it's a workload that may be just running on-prem in a large enterprise or a workload that is moving to cloud or sometimes to multiple clouds for resiliency, that transformation in speaking to a large telecommunications company, a large healthcare company, a large tech company, and I can cite you many other examples, I was pretty overwhelmed to understand that those transformations are still going on. That is just a recent conversation I had with CTO of a large telecommunications company who said that they are moving 1300 plus applications to another hyperscaler and trying to determine which workloads are best suited for MongoDB.

So the whole multi-cloud or a public cloud transformation is still going on and just my intuitive sense in speaking to these customers will be going on for at least next five to seven years. So that specific TAM still very much exists for MongoDB. Now, these are the same set of customers, while they are trying to modernize their application stack, they are also experimenting, I would say, because I have not seen agents at scale that are customer-facing or sometimes even employee-facing. They may have 10, 15, 20, but not that many compared to thousands of applications they run. In those AI applications area, they are experimenting sometimes with our embedding models or with our vector database or using MongoDB for real-time operational database. So that second aspect, which is still fairly early, but we are very well positioned as you think about AI workloads in enterprises and large enterprises.

And last but not the least, spending time, as you know, or you may know, that I spend half of my time in New York City and half of my time in Silicon Valley, and speaking to my network in Silicon Valley with AI-native companies or digital-native companies, what I hear from them is that certain alternatives and relational database just do not scale because AI workloads are fundamentally around unstructured and semi-structured data. And then they decide sometimes explicitly to use MongoDB. So I put this in three buckets. One bucket is our core, and still the cloud transformation, digital transformation, modernization, whichever term you want to use, our core will still continue to grow. As people create AI agents at scale, MongoDB has a role to play. And for AI-native companies, and some at scale, are already using MongoDB because the alternatives in relational world just do not scale. So those are my three buckets and initial mental model on how these conversations are proceeding and what we can do for them.

Analyst Matt Martino (Goldman Sachs): Really clear. Thanks for sharing your thoughts there, CJ. And then, Mike, just a quick follow-up for you. It was good to see the outperformance on both Atlas and non-Atlas. But, you know, with margins now about 200 basis points shy of your midterm framework, how should we think about the philosophy around reinvestment and any considerations around non-Atlas and the ability to expand margins as we look out into fiscal 27?

Executive Mike Gordon (CFO): Thanks for the question, Matt. I'm sure everyone's focused on 27, so what we'd say is we will guide 27 on the next call. What we would say is, and it's built into the guidance that you have in Q4, and I also talked about it on the prepared remarks, we are continuing to invest and we will continue to invest. Some of the investments that we wanted to make, especially around engineering, marketing less so, but certainly around sales capacity, has been pushed into Q4. So you should expect to see OpEx continue to grow in fiscal 27. But we also want to make sure, and that's why, Matt, we took the time to say, hey, we want to reorient you to what we talked to you about in September. We still expect to see margin expansion. But you really see it in the fiscal 26 numbers is that is coming mostly from revenue growth. That is the expectation next year. We'll continue to grow revenue. We're going to continue to invest in the business, but the business model will continue to drive that expansion. So you should expect to see us continue to invest, especially across those three areas.

Analyst Matt Martino (Goldman Sachs): Thanks, Mike.

Analyst Carl Karstad (UBS): Okay, great. Thank you. First of all, CJ, welcome aboard. I'm excited to work with you over the coming years. I had a question for you. So it seems as if you're describing these good set of numbers as strength in the core, essentially even before that AI tailwind kicks in. I'd love if you could define what you think is fundamentally driving that core strength. And do you feel like it's possible that actually Mongo is already getting an AI tailwind in the sense that there's a heightened focus on modernizing your data in advance of AI such that this core strength is actually AI related?

Executive CJ Desai (CEO): Carl, great to hear from you and looking forward to seeing you on Wednesday. I would say the core strength from my perspective is workloads that are, you know, need modernization has a lot of unstructured or semi-structured data and ideally suited for MongoDB. Now, when it comes to AI, could AI potentially drive more modernization efforts, that is possible but not deterministic. As in, we see, as we shared in the remarks, that in the high end of the enterprise, the consumption of the workloads we acquired maybe a year ago, a year and a half ago, that continues to move up in the right direction as our go-to-market teams are focused on the high end of the enterprise. We also saw broad-based strength in Europe, and that is pretty much to the core business like the large insurance company on the claims engine and other things that I spoke about related to policies.

So I particularly see that as, okay, does that mean that if core is modern, it helps with AI workloads? Absolutely, that is true because they are not mutually exclusive. And, Carl, one thing I would say, this is my personal experience in building systems AI technologies in the past, that the AI team is typically a separate team from the core data team. An AI team relies on the core data team, and if the core data team moves slow, then AI teams get really frustrated because innovation velocity is how they measure themselves on. So my personal experience was, hey, when the core team is not agile, their schemas are not flexible, it actually slows AI down. So there is definitely some facts behind your theory that it is potentially the AI revolution, which we are still in the early stages, is driving modernization in the other part of the enterprise.

Analyst Carl Karstad (UBS): Okay, CJ, thank you. And then, Mike, for you, I think everybody on the line appreciates the more definitive guidance on Atlas for the following quarter, so thank you. I wanted to ask what's driving that. Is it simply a function of you and Jess in your relatively new seats wanting to be more transparent in the guidance? Or, Mike, is there something actually changing in Atlas such that now that it's at scale, it's becoming predictable enough that it now makes more sense to give precise guidance?

Executive Mike Gordon (CFO): So thanks, Carl. Thank you for the question. I would say it's probably a little bit of both. One is, hey, we want to give you folks a little bit more visibility to what's behind the guidance that we provide. That was number one. Also, as Atlas gets to be, gosh, now almost a $2 billion business, you know, we feel better about the forecasting. The team has done a wonderful job forecasting that part as well. So when we gave the number for Q4, we want to make sure and give you the visibility. But we also have a pretty good view of what we hope it would be. Understanding that, keep in mind, Q4, we want to be prudent because there are some seasonal holiday patterns that can be somewhat unpredictable. And we've seen that play out in the past Q4s. So I just want to note that for the guidance that we just gave.

Analyst Carl Karstad (UBS): Got it. Thank you.

Analyst Remo Linschao (Barclays): Thank you, CJ. All the best from me as well. I have two questions, one for CJ, one for Mike. CJ, one of the core things in terms of adoption of Mongo will be on the developer side because they're at the end of the day, developers are a big driver of what's getting used, etc. At the moment, a lot of AI is on the West Coast. What's your thinking around getting developer engagement up with Mongo to go against that Postgres narrative that happens a lot in the Valley? And then, Mike, for you, since next year, EA... is not seeing benefits for multi-year. Should we anchor our numbers on the ARR performance then? Is that the right way to think about it?

Executive CJ Desai (CEO): Thank you, Remo. Great to hear from you. I'm going to first ask, there is a little bit historical context in terms of your point on the West Coast. I'm going to ask our previous CEO, David Tacharia, to talk about Reclaim the Bay, the initiative that him and the team started. And then I'm going to specifically talk about how I think about it on the West Coast.

Executive David Tacharia (Former CEO): Hey, Raimo, it's Dave here. As CJ mentioned, we've talked about this in previous calls, but we made a concerted effort to reinvest in the Bay Area because during COVID and post-COVID, we felt that we had neglected that region. And obviously, there was a whole new corpus of AI-native companies that were getting launched. So there's been a real concerted effort, both in terms of putting more feet on the street putting more marketing efforts in terms of supporting that part of the world, investing more in the startup community and also in the venture community to get people to understand the true value proposition of MongoDB. We've done things like hackathons and other events in that area as well. And there's a team really focused, dedicated to really supporting and servicing these early AI native companies and that is starting to yield some results. And we feel really good about the progress there, but I'll let CJ talk about what happens going forward.

Executive CJ Desai (CEO): Thank you, Dave. And this is the Reclaim the Bay in San Francisco area on the West Coast. It is 100% true, Remo, that there is a lot of investment with AI-native companies, and we could benefit from increased mind share and being in front of them, as in the developer community that you talked about, which is a super important community to us, on the West Coast. So me spending personally time on the West Coast Health, I do also have deep network in the West Coast community, both venture community as well as tech companies at scale, and I've already started leveraging that network to get their feedback. We are really excited in this quarter as in the 4Q, we are relaunching our DOT Local after a few years in San Francisco on January 15th, where we are going to invite companies that have built on MongoDB, some great speakers on why they should build on MongoDB, and show hands-on experience to the developer community in that conference on January 15. And what I see is, you know, just speaking to many CEO founders as well as developers of smaller companies or mid-sized companies, that all these efforts of the marketing investment that Mike and Dave originally approved is going to start yielding results as we move into the next fiscal year.

Analyst Remo Linschao (Barclays): Thank you. And, Ramo, thanks for the question. It's Mike. On non-ATLAS next year, we wanted to make sure we've had a lot of questions about the multiyear headwinds, so thank you for the question there. We are not guiding for fiscal 27. However, sitting here today, I would steer you more towards if you look at the full year revenue growth of non-Atlas, it's about 4%. Somewhere in that mid kind of low single digits is probably a good range to think about for next year as we sit here today.

Analyst Remo Linschao (Barclays): Okay, that's clear. Thank you.

Analyst Brad Reback (FIFO): Great. Thanks very much. Not sure who this is for, but on the commentary around new customer strength within Atlas, are you seeing new customers ramp faster for net new workloads than they have been historically? And if so, why?

Executive Mike Gordon (CFO): Brad, my initial observation is that the team needs engineering team has done a fantastic job when they launch 8.0 and all the subsequent point releases. That allows Atlas to be adopted faster and remove the friction, whether you are coming via our self-serve channel or whether you are a large enterprise moving on to Atlas. So that's one thing I would say. And I'm going to ask Dave to provide commentary as well from a context perspective.

Executive David Tacharia (Former CEO): Yeah, I think what I would also say is that, Brad, is that I think the self-serve team has really removed the friction to enable customers to onboard more quickly and more easily. And given the performance, price performance gains that we've seen in 8 and now even better in 8.2, I think that's really driving a lot of the traction we're seeing in our new customers. They quickly see the performance benefits and they're scaling nicely. And so that's allowing us to continue to acquire customers efficiently. And one last thing on that, Brad. If you look at the revenue from that, it hasn't changed materially. It's still, keep in mind, a pretty small number when they first onboard, so it's not going to move the needle much. We haven't seen much change in that cohort over the last couple of years.

Analyst Brad Reback (FIFO): Great. And then, CJ, a quick follow-up for you. Philosophically, how do you think about M&A as it relates to Mongo? You know, what types of things, if anything, do you think you need to acquire?

Executive CJ Desai (CEO): Brad, you know me well, and I'm a big believer in organic growth. Dave and the team have laid a very strong foundation on our technology platform. I think Voyage AI in February was a brilliant acquisition where we got an unbelievable team in Palo Alto. My goal on behalf of MongoDB is to always believe in our own teams and our technology, we participate in a large market, and where it makes sense where we can get a particular adjustment technology or a great team that can help us accelerate the roadmap, we would always consider that type of M&A.

Analyst Alex Zukin (Wolf Research): Hey, guys. Thanks for taking my question. CJ, maybe for you, I mean, you shared, I think, a lot of thoughts about your initial vision. You shared the three pillars of the core, the enterprise AI opportunity and the AI natives. I just want to maybe lean in. Where do you see your particular skill set and network offering kind of not the lowest hanging fruit, but your ability to make kind of the biggest impact in call it the next 12 to 24 months? Like, where do you really see that incremental opportunity for growth inflection?

Executive CJ Desai (CEO): I would say, Alex, and, you know, you are aware of the enterprises and the customer obsession I have and the relationships that I have formed over many, many years with the technology leaders at large companies. So from my perspective, there are two areas where I can benefit our go-to-market teams immensely. Number one is Fortune 500, where MongoDB can still penetrate even at a higher rate than it is penetrating today, both within the existing accounts as well as the new accounts we get. So that's Fortune 500. And then I was with our sales teams in Europe and there are many customers that they are targeting, including existing customers, large banks, manufacturing companies, and so on, where they're trying to expand, where my personal relationships with those technology buyers can help. So that's bucket number one, is make no mistake, high end of the enterprise, as in Fortune 500 and Global 2000.

Number two, on the other extreme, would be AI-native companies lived in Silicon Valley for a very long time. I understand where the venture community is investing. Folks who are creating, whether it's domain-specific AI companies or foundational companies, have relationships there as well across 101, 280, and 237. And that's where I also plan to, I would say, plant the seeds in a correct fashion so that over time that becomes a meaningful business for MongoDB if we are the underlying infrastructure for those companies. So those are the two extremes that I'm going to spend personally a lot of time on.

Analyst Alex Zukin (Wolf Research): Excellent. And you mentioned Voyage AI, the acquisition this year being kind of a crown jewel in the portfolio. Maybe just help us understand with the AI native, specifically the opportunities there, are those starting? Are you guys landing with Voyage? Are you landing with Atlas? Are you landing with both now at a more kind of constant pace? Help us understand kind of that incremental differentiator.

Executive CJ Desai (CEO): Yeah. I would say one example, and this, you know, in my remarks I shared, that there is a super high growth AI company that is doing very, very well and will become a very large company. I have absolutely no doubts about that. They were not able to scale with Postgres and few other technologies, Redis and so on that they were using, and they moved completely to MongoDB. Seeing that week over week and month over month growth, is super inspiring, and I spoke to the hyperscaler where this workload is running, and they are seeing the same that, wow, this company is doing really well.

So that's built on MongoDB because Postgres had scaling issue. The other extreme, I spoke to a fairly successful AI native company that is doing decent ARR, growing very fast, and when I said, hey, have you considered MongoDB to the founder CEO who is very technical. He said, CJ, we built our own vector database and so on. And while I was speaking to him, Alex, about 10 days ago, he basically said, once he looked at the portfolio, he said, let me start with embeddings first. So we are going to try. Of course, we have to prove it to him by our embeddings improves his accuracy on search and so on and improves the performance. So he said, let's start with embedding models first from OAJI. Once that works, CJ, I'm willing to replace my vector DB that we have homegrown, created it with MongoDB. And oh, by the way, if that works well, eventually I'm willing to swap out my operational database as well and use MongoDB.

So in those kind of scenarios where they are already on a certain track, we can land with Voyage AI embeddings. And I'm also seeing in a very large customer of MongoDB, I spoke to somebody who is running the AI initiatives, and they love the Voyage AI embeddings and re-ranking model, and they've already approved it for two big workloads. So we can absolutely land with that is the short answer.

Analyst Ryan McWilliams (Wells Fargo): Hey, guys. Thanks for the question. The consumer app development environment seems to be getting stronger as new iOS app development has surged to multi-year highs. We think it's due to agenda coding, and I know it's early. But on the enterprise side, are you seeing stronger product velocity from your customers in building their enterprise applications?

Executive David Tacharia (Former CEO): I'm going to ask Dave to provide his opinion, and then I'll provide mine.

Executive David Tacharia (Former CEO): Yeah, I think what we're seeing is we're clearly seeing a lot of, I would say, prototyping and iteration. I would say the enterprise requirements still have pretty strong and stringent requirements around security and durability and performance. So while there's a big difference between coming out with a prototype and having a production-grade system that an enterprise can truly rely and trust, and so there is still a lot of work required to, you know, make those applications enterprise class. But clearly with the advent of code gen tools, the rate and pace of software development is only going to increase. And as I think we said in the past, that's one of the big reasons why we think AI is a tailwind. It's just that, you know, the ability to produce more software and more and more strategies is then encapsulated in software. So from that point of view, we think that's all good news for us.

Executive CJ Desai (CEO): Yep. And the only thing I'll add on is when I speak to customers who have been speaking for a long time, you know, in regulated industries, which is financial services, which is healthcare, which is public sector, the requirement for an AI agent to be in production versus prototype are vastly different. And they are looking for governance, auditability, this and that, while the innovation is and the need for the speed is very high. So I have not seen, like, you know, customers will tell me, CJ, I have 10 agents in production, 15 agents in production, and when I really ask them, I say, are they really customer-facing? Can they be audited on the you know, probabilistic outcome they derived, the answer is, oh, we are still working through that. That doesn't mean that it will not happen soon or it will never happen, but I still feel we are fairly early. And even the environment on which they are building agents, they are telling me they try one, it doesn't work, they move on to the next one. So the churn for some of these AI companies that deliver these tools is also very real. And that's why I'm very encouraged by the MongoDB opportunity. We have the platform for operational data. We have the best vector database, and we have the embedding models where they can comfortably, at enterprise scale, build a real AI agent using MongoDB platform.

Analyst Ryan McWilliams (Wells Fargo): Excellent. Really appreciate that detail. And then for Mike, on the Atlas 4Q growth guidance, appreciate the color there. Just a quick clarification there. On this 4Q Atlas guidance, should we expect results closer to 10 or a guidance philosophy consistent with your historical precedent?

Executive Mike Gordon (CFO): Yeah, so thanks. So I don't want to go into the golf analogy. And besides, Ryan, you know I like hockey analogies better. What I would say is that, hey, we feel really good about Atlas. It's had a great year so far. We feel good about it going into Q4. We remain excited about the growth. That being said, we are being prudent for Q4. As the seasonal holiday patterns, hey, they can be somewhat unpredictable, and we've seen that play out in the past Q4s. So what I would say is, hey, we just need to be prudent as we enter the holiday season.

Analyst Ryan McWilliams (Wells Fargo): Sounds like you're getting pucks on the net. Thanks, guys.

Executive CJ Desai (CEO): Thank you, Lisa. In summary, we delivered an exceptional third quarter, highlighted by accelerating Atlas growth, robust customer additions, and significant operating margin output. We are raising our revenue and operating income guidance for the fourth quarter and full fiscal year 2026, and reiterating our commitment to the long-term financial model we outlined at Investor Day. Our results underscore that MongoDB's core business is firing on all cylinders even before any meaningful AI tailwinds. At the same time, we are uniquely positioned to become the generational modern data platform for the AI era, all while driving durable, efficient growth. Thank you, everyone, for joining, and thank you for listening. This concludes today's conference call. You may all disconnect.