MongoDB, Inc. (NASDAQ:MDB) Q4 2026 Earnings Call Transcript

MongoDB, Inc. (NASDAQ:MDB) Q4 2026 Earnings Call Transcript March 3, 2026

Operator: Good day, and thank you for standing by. Welcome to MongoDB’s Fourth Quarter Fiscal Year 2026 Earnings Conference Call [Operator Instructions]. Please be advised that today’s conference is being recorded. I would now like to hand the conference over to your first speaker today, Jess Lubert, VP of Investor Relations. Please go ahead.

Jess Lubert: Thank you, operator. Good afternoon, and thank you for joining us today to review MongoDB’s fourth quarter and full year 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 CJ Desai, President and CEO of MongoDB; and Mike Berry, CFO of MongoDB. During this call, we will make forward-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 multiyear license revenue, the long-term opportunity of AI, our financial guidance and underlying assumptions and our investments and growth opportunities in AI.

These statements are subject to a variety of risks and uncertainties, including the results of operations and financial conditions that could cause actual results to differ materially from our expectations. For a discussion of material risks and uncertainties that could affect our actual results, please refer to the risks described in our quarterly report on Form 10-Q for the quarter ended October 31, 2025, filed with the SEC on December 2, 2025. Any forward-looking statements made on this call reflect our views only as of today, and we undertake no obligation to update them, except as required by law. Additionally, we will discuss non-GAAP financial measures on this conference call. Please refer to the tables in our earnings release on the Investor Relations portion of our website for a reconciliation of these measures to the most directly comparable GAAP financial measures.

With that, I’ll turn the call over to CJ.

Chirantan Desai: Thank you, Jess, and thank you, everyone, for joining us today. To begin, I would like to provide some observations from my first full quarter at MongoDB. Over the last 100 days, I have spoken to more than 200 customers globally, spanning from AI natives to Fortune 500 enterprise customers that are leveraging the MongoDB platform to drive innovation that is critical to their business. Whether it’s an AI or digital native looking for a highly performance solution that dynamically scales, a large enterprise looking for multi-cloud resiliency for their modern mission-critical applications or a customer seeking an integrated offering for AI agents with features such as search, vector search and embeddings in a single intelligent data layer, customers are excited about the strength of the MongoDB platform.

My key takeaway is that MongoDB’s foundation is in great shape, and the company is well on its way to become the generational data platform of choice in the AI and multi-cloud era. Now on to this quarter’s results. We generated total revenue of $695 million, up 27% year-over-year, beating the high end of the guidance by 4%. Top line strength was driven by Atlas, which grew 29% year-over-year crossing the $2 billion run rate mark for the first time and generating a record $114 million in net new revenue in the quarter. Non-Atlas grew 20% year-over-year, our best growth quarter in the last 2 years. We signed several large deals in the quarter, including an approximately $90 million transaction with a large tech company that plans to expand both core and AI workloads on Atlas and a greater than $100 million transaction with a large financial institution for Enterprise Advanced referred as EA, representing the largest TCV deal in the history of MongoDB.

We delivered a non-GAAP operating margin of 23%, more than 100 basis points above the high end of guidance. We ended the quarter with over 65,200 customers, adding 2,700 customers in Q4, growing both year-over-year and quarter-over-quarter. This brings our full year customer additions to 60% year-over-year increase. While AI is not yet a material driver to our results, we are encouraged by the growth we are seeing with customers leveraging our AI capabilities. The number of customers leveraging vector search has nearly doubled year-over-year and the number of customers using Voyage embedding models has also doubled since the acquisition last February. This growth is across a diverse range of customers, AI natives, digital natives and large enterprises.

We finished fiscal 2026 on a high note, with strength in Q4 driven by our continued go-to-market execution and the broad-based demand we have seen across the business. Our teams generated record new ARR in Q4, an acceleration of that metric in fiscal ’26, highlighting the strength of both our upmarket and self-service motions. Our EMEA team had an especially strong Q4, generating record new ARR driven by wins at major financial institutions, large retailers and leading tech companies. At the same time, we outperformed on operating margin, achieving above a Rule of 40 performance and demonstrating that we can drive durable revenue growth while simultaneously expanding margin. Through my conversations with customers, a clear theme emerged. Large enterprises are increasingly standardizing on MongoDB to power a wide spectrum of workloads, including both core mission-critical applications and emerging agentic AI applications.

Rather than treating AI as a stand-alone initiative, many are expanding their use of us as a strategic data platform that supports both foundational workloads and their next generation of intelligent applications. For example, MongoDB continues to power a wide range of workloads, including high-volume transactional systems, real-time applications and emerging AI workloads across multiple lines of business at JPMorgan Chase, the world’s largest financial institution. The scale and breadth of our partnership with them reinforces our ability to serve as a strategic data platform for the most demanding enterprises. We see tremendous opportunity to expand within our existing Fortune 500, Global 2000 and AI native customer base, where I’m actively leveraging my relationships to open new doors, engage the C-suite and drive strategic expansion conversations top-down.

MongoDB is increasingly recognized as the architectural foundation powering innovation for frontier model companies, leading digital natives expanding into AI and AI native organizations scaling globally. The database layer has endured through multiple technology shifts over the past 60 years, and it is even more critical in this AI shift. AI and agentic applications require memory, state and high-quality retrieval, capabilities native to our modern OLTP platform, which powers real-time applications without ETL or bolt-on systems through integrated search, vector search and embeddings. In this platform shift, OLTP is the high ground and MongoDB is purpose-built to win. Notably, Emergent Labs, a leading AI wide coding platform in India that just crossed $100 million run rate, selected Atlas over PostgreSQL to power AI agents that build production-ready applications from natural language prompts.

They power nearly 6 million applications built across 190 countries and handle applications that average 35,000 lines of code with some reaching $300,000, all made possible with Atlas’ flexible document architecture and reliable scale. We are also fueling innovation at AI-native Customer ElevenLabs, which is redefining conversational AI with its new enterprise agent platform. ElevenLabs selected Atlas to power the critical long-term memory and knowledge base for their autonomous agents. By leveraging Atlas Search and vector search, they enable their agents to retain complex context and deliver highly personalized interactions in real time and at global scale, supporting their rapid expansion to $330 million of ARR and $11 billion valuation.

Another tailwind is the renewed importance of on-premises deployment in enterprise architectures. Many large customers, particularly in regulated industries such as financial services, telecommunications and government, view EA as mission-critical and are making long-term commitments that reflect the need for operational resilience and support for data that will not move to the public cloud. Consequently, I’m confident in the durability of our EA business. Pursuing feature parity to Atlas and continued go-to-market momentum are key priorities as we move forward. For example, Axon Networks, a global leader in telecom network management serving 32 telcos and over 90 million homes and enterprises selected EA as the foundation for its operator as a Service platform.

This platform delivers a real-time digital twin and API-first architecture designed to handle massive data peaks and high-volume time series workloads. EA provides the flexibility to run across mission-critical environments, including hyperscalers and bare metal, along with the enterprise-grade security and operational tooling required to support Axon’s AI-first autonomous networking platform at scale. What is truly compelling about our platform is that these tailwinds serve as a powerful force multiplier for one another. The combined power of these capabilities, the flexibility of the document model, the performance and scale of Atlas, the ability to run anywhere and our integrated AI functionality is what really resonates with our customers.

A marquee example of the platform in action is Adobe, which expanded its strategic partnership and long-term commitment with us to accelerate AI-driven innovation. MongoDB now underpins a range of Adobe’s key initiatives, including agent experiences powered by Atlas Vector Search and soon voyage embeddings. Adobe leverages Atlas to manage large fleets and always-on database deployments at global scale, while also continuing to partner with us for support of self-managed business-critical workloads on EA, highlighting our ability to operate seamlessly across both cloud and on-prem environments. After spending time with 200 customers, partners and our go-to-market teams globally, it has become increasingly clear that we have a massive opportunity ahead of us.

The strength of our platform and the depth of our customer relationships is a direct reflection of our exceptional global team, and I’m proud to say we have world-class talent across engineering, go-to-market and G&A functions. During the upcoming year, my focus will be to build upon what’s already working by: first, remain relentlessly customer-focused to deepen strategic partnerships and accelerate growth, particularly across large enterprises and AI native customers here in Silicon Valley. Second, accelerate our innovation agenda by empowering product and engineering teams to build the generational multi-cloud data platform for the AI era. Third, thoughtfully scale our self-serve motion to expand adoption across the long tail with a disproportionate focus on AI native companies.

Fourth, drive operational excellence across go-to-market, product and G&A to enable our teams to perform at their best while sustaining durable, profitable growth. Finally, I wanted to provide an update on our go-to-market leadership. Effective tomorrow, March 3, 2026, Erica Volini joins MongoDB as our Chief Customer Officer reporting directly to me to accelerate our next phase of growth. Erica brings a rare blend of experience serving large enterprise customers at Deloitte and scaling go-to-market growth at ServiceNow. At MongoDB, she will focus on accelerating our partner growth engine, deepening our enterprise footprint and ensuring a seamless world-class experience across the entire customer life cycle. As noted in our earnings press release, Cedric Pech, President of Field Operations; and Paul Keppambesis, Chief Revenue Officer, are leaving MongoDB.

We have been thoughtfully planning this transition for some time, and we believe now is the right moment for this change. I want to extend my sincere gratitude to both Cedric and Paul for their contributions over the last decade. They were truly instrumental in building our go-to-market foundation. Looking ahead, we have a deep bench of go-to-market talent, and the team is well positioned to execute against our objectives without disruption. We are in the latter stages of a search for a new CRO. The caliber of these candidates is a testament to our momentum and the significant opportunity ahead. Paul will remain CRO through Q1 and serve as an adviser through Q2 to ensure a seamless transition to the new CRO. With that, I’ll now hand the call over to Mike Berry to discuss the financial results in greater detail.

Michael Berry: Thank you, CJ, and good afternoon to everyone on the call. I will begin with a review of our fourth quarter fiscal ’26 results and then finish with our outlook for the first quarter and full year fiscal ’27. In order to spend more time on the fiscal ’27 outlook, I’ll be a little more concise on my fourth quarter comments. I will be discussing both GAAP and non-GAAP results. As CJ mentioned, we had another strong quarter as we exceeded all of our guidance ranges and finished our fiscal year on a high note. In the fourth quarter, total revenue was $695 million, up 27% year-over-year and above the high end of our guidance. Our income from operations was $159 million for a 23% operating margin compared to 21% in the year ago period.

We achieved positive GAAP operating income in the fourth quarter. We are very pleased with our stronger-than-expected operating margin results, which benefited entirely from our revenue outperformance. Net income in the fourth quarter was $143 million or $1.65 per share based on 86.5 million diluted shares outstanding. This compares to net income of $108 million or $1.28 per share on 84.6 million diluted shares outstanding in the year ago period. Shifting to our product mix. Atlas revenue momentum remained strong with year-over-year growth of 29% in the fourth quarter, which accounted for 72% of total revenue, up from 71% in the year ago period. Atlas growth was driven by continued strength with our largest customers in North America and Europe, where we saw strong momentum with growth of new and existing applications.

We believe this strength reflects the growing strategic importance of Atlas to many existing customers and is a positive indicator of future growth. You can see the success with existing customers in our total company net ARR expansion rate, which increased to 121% in the fourth quarter, up from 120% last quarter and 119% a year ago. Turning to non-Atlas. We experienced strong momentum during the fourth quarter, driven by strength with financial services, public sector and technology customers that are choosing to build with MongoDB long term for their most mission-critical applications. This resulted in strong multiyear revenue and non-Atlas ARR, which reflects the underlying revenue growth of this product without the impact of changes in duration.

Non-Atlas ARR grew 13% year-over-year, reflecting the momentum we are seeing in the business. The strength in non-Atlas also resulted in a higher-than-expected number of larger deals with bundled Atlas and EA products. This resulted in a greater-than-expected attribution of revenue to EA versus Atlas in the fourth quarter. Adding back this impact, Atlas growth would have been approximately 30%. We are encouraged to see more of our customers growing on both Atlas and EA and believe these deals illustrate the strategic importance of having both cloud and on-prem solutions for many of our largest customers. You can see the strength in the growth of deferred revenue as well as the growth in RPO, which grew from $748 million at the end of fiscal ’25 to $1.47 billion at the end of fiscal ’26, a year-over-year growth of 97%.

We ended the quarter with 2,799 customers with at least $100,000 in ARR and 402 customers with at least $1 million in ARR, representing 17% and 26% year-over-year growth, respectively. For each of these cohorts, ARR is growing even faster, reinforcing the benefit of our upmarket focus. Of our Atlas customers generating at least $100,000 in ARR, 44% are leveraging 2 or more features of our platform, which is up from 36% in the year ago quarter. Average revenue from these platform customers is meaningfully higher on average as compared to the rest of the Atlas space, illustrating the benefit of our platform capabilities. Turning to the balance sheet and cash flow. We ended the fourth quarter with nearly $2.4 billion in cash, cash equivalents, short-term investments and restricted cash.

We spent $55 million to repurchase approximately 133,000 shares and used $60 million for the cash settlement of taxes on employee RSUs. Operating cash flow remained strong at $180 million, and free cash flow was $177 million, which compares to $51 million and $23 million, respectively, in the year ago period. Our cash flow results were driven primarily by strong operating profit and improving working capital dynamics, particularly related to higher cash collections, mainly driven by the higher-than-expected multiyear EA deals. Now I’d like to share a few guiding principles and some of the assumptions underlying our outlook for Q1 and fiscal ’27. To begin, we continue to believe in the long-term model presented at Investor Day last September and remain committed to growing Atlas by greater than 20% and being a Rule of 40 company.

We will achieve this goal through a combination of revenue growth and margin expansion. But to be clear, revenue growth will be the main driver of improved profitability. Our outlook assumes the business environment remains relatively stable, and we operate under similar conditions to what we experienced over the course of the past fiscal year. As I mentioned at our Investor Day in September, we have not changed our guidance philosophy as we will provide an outlook with more upsides than downsides specifically related to the EA business. We are early in the year, and we want to be mindful there could be risk that we do not have line of sight to at this time. Now let’s get into the details. Starting with Atlas. We have continued to see strong momentum and experienced relatively consistent consumption growth through the course of the past year.

We expect these trends to continue through fiscal ’27 and would also note that as Atlas has grown larger, this has helped limit the volatility from specific customer cohorts. Based on our continued confidence in our market positioning, customer feedback and product advantages, we currently expect to see Atlas revenue growth of approximately 26% in Q1 and 21% to 23% in fiscal ’27. This outlook reflects our continued confidence in Atlas while taking into account we are a consumption business and visibility is more limited in the back half of the fiscal year. For non-Atlas, we have continued to see healthy ARR trends, and we have been positively surprised by the momentum we experienced with large multiyear deals in fiscal ’26. While we remain optimistic regarding our ability to grow this business over the long term, it remains difficult to predict, and we will only include deals in our forecast that have either closed or have a high probability of closing to limit the risk of a negative surprise.

At this point, we expect our non-Atlas business to see mid- to upper single-digit growth in Q1 and low to mid-single-digit growth in fiscal ’27, which reflects our belief that the impact of duration will neither be a significant headwind or tailwind to growth for the year. In terms of AI, we remain optimistic regarding our opportunity and are seeing encouraging trends with a number of AI natives. While this subset of customers has significant potential, many of them remain early in their MongoDB journey and are not yet meaningful drivers of revenue. Turning to profitability. We remain committed to driving revenue growth and expect to expand operating margin by 100 basis points in fiscal ’27. We will achieve this expansion while investing for growth.

Some of these investments include enhancing our AI capabilities, further integrating Voyage, bringing feature parity to EA relative to Atlas, building out our presence in Japan as well as strengthening our U.S. federal business. We will also continue to invest in marketing programs, developer awareness and select quota-carrying headcount. With respect to cash flow, we made meaningful progress in cash management during fiscal ’26 with our operating cash conversion exceeding 100% and up significantly from the approximately 50% experienced in fiscal ’24 and ’25. This remains a key area of focus, and we would expect cash flow to remain healthy in fiscal ’27. We currently expect cash conversion in the 80% to 100% range during the upcoming year and on a longer-term basis, which is in line with our long-term model.

Finally, we will continue to execute our share buyback program to partially offset dilution from employee equity awards and settle the taxes due on the vesting of employee RSUs with cash instead of issuing new shares. In fiscal ’27, we currently plan to commit 100% of our free cash flow to these 2 actions and will also benefit from the settlement of over 1 million shares of stock for the cap calls associated with our 2026 notes that matured in January ’26. We will continue to manage share count prudently for the long term and demonstrate our commitment to being good stewards of your capital. Now let’s shift to guidance for the first quarter and fiscal ‘ 27. For the first quarter, we expect revenue of $659 million to $664 million, which equates to 20% to 21% year-over-year growth.

We expect non-GAAP income from operations to be in the range of $105 million to $109 million for an operating margin of approximately 16.5% at the high end. We expect non-GAAP net income per share to be in the range of $1.15 to $1.19 based on 86.2 million diluted shares outstanding. For fiscal ’27, we expect revenue to be in the range of $2.86 billion to $2.9 billion, representing full year revenue growth of 16% to 18%. We expect non-GAAP income from operations of $545 million to $565 million for an operating margin of approximately 19.5% at the high end of guidance. We expect non-GAAP net income per share to be in the range of $5.75 to $5.93 based on 86.7 million diluted shares outstanding. Note that the non-GAAP net income per share guidance for the first quarter and fiscal ’27 assumes a non-GAAP tax provision of 20%.

To summarize, we had another strong quarter and feel very good about the business heading into fiscal ’27. We are pleased with our ability to drive both revenue growth across the business while expanding operating profit and driving meaningful free cash flow. We remain incredibly excited about the opportunity ahead, and we will continue to invest responsibly to drive long-term shareholder value. With that, operator, we would like to open it up for questions.

Operator: [Operator Instructions]. And our first question comes from the line of Raimo Lenschow of Barclays.

Q&A Session

Raimo Lenschow: 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 the doing is like to increase mind share again, like share a little bit your experiences there? And then one for Mike. On EA, next year had a bigger cohort than this year, I’m just wondering if the strength in the second half of this year, was that earlier renewals for next year? Or is the cohort still in place?

Chirantan Desai: Thank you, Raimo. Appreciate it. So January 15 event, our dot local San Francisco, I would consider a great success and I would put that in 2 buckets. Number one, we exceeded even though it was a week day, many, many founders, builders who came to the event, and there was a long line outside for people to get into the conference that give me really, really good feeling that we invested in the right area. Number two, when we looked at the attendees, Raimo, 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 dot local in San Francisco, again, in August this year, which we have not done before based on the success. Mike?

Michael Berry: Thank you, CJ. Raimo. Thanks for the question. So on EA, a couple of things. So we’re super excited about the year we had fiscal ’26 was a very strong year and especially Q4, not only in the run rate business, but obviously, all the multiyear deals. So 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.

Operator: Our next question comes from the line of Matt Martino of Goldman Sachs.

Matthew Martino: 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.

Chirantan Desai: 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 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 Main Street 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 AI native companies, which is hardly.

Matthew Martino: Okay. Very clear. And then Mike, maybe for you, just a couple of major EA deals were announced this 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?

Michael Berry: Yes. Thanks for the question, Matt. So as we talked about — so 2 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 bundled 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.

Chirantan Desai: And Matt, I would say in speaking to customers, because this conviction is over a large set of very important customers that is definitely the trend that I’m speaking from our customers is, number one, that because of a 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 their critical data estates on-prem. And this is not just only in financial services, we are seeing that in health care and other verticals like government. But when I was in Europe and even in Asia, I’m also seeing there 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.

Operator: Our next question comes from the line of Jason Ader of William Blair.

Jason Ader: 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.

Chirantan Desai: 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.

Jason Ader: Okay. Great. And then just one quick follow-up on that. Just is 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, CJ?

Chirantan Desai: Jason, we do have ambitious road map, 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 road map 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 that 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.

Operator: Our next question comes from the line of Ryan MacWilliams of Wells Fargo.

Ryan MacWilliams: CJ, great to hear about Anthropic as a customer at the MDB local event. I’d 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. Would love to hear why you think MDB architecturally is best suited for these growing types of AI use cases.

Chirantan Desai: Absolutely. Ryan, 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 this AI native companies without realizing that they will run into scale issues or potentially there was one of the choices that people could have gone with as an AI native companies 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, right 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 rights that as you scale your AI native company, they can rely that MongoDB will scale with them.

Ryan MacWilliams: 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 onetime items in the quarter besides the Atlas and EA bundling?

Michael Berry: Yes. Thanks, Ryan. So looking back at Q4, the holiday seasonality played out largely as we expected. There were really no surprises or deviation from the historical trends. So it largely played out as we expected.

Operator: Our next question comes from the line of Karl Keirstead of UBS.

Karl Keirstead: Mike, let’s stick to Atlas in the fourth quarter. A couple of questions. One was the 2-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?

Michael Berry: Sure. So all right, let’s take a step back, Karl, 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 bundled thing. I’ll talk about that in a second, 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.

There’s — we always do bundled 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, Karl, that did move the needle.

Karl Keirstead: Okay. That’s helpful. Yes. And then maybe, Mike, as a quick follow-up. 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.

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

Operator: Our next question comes from the line of Ittai Kidron of Oppenheimer.

Ittai Kidron: Michael, I want to follow up on the last questions here mainly around EA. Clearly, you had a very strong fourth quarter here with 2 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.

Michael Berry: 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 and 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 a lot of moving parts here. The biggest variability to the business is not the cohorts, it’s what ends up closing as a multiyear deal versus a 1-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 than 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 multiyear 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.

Ittai Kidron: 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 count structure that you’re thinking about also in light of who you’re looking for as far as the CRO is concerned?

Michael Berry: Yes. 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’s 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.

Chirantan Desai: And Ittai, what I would tell you is that personally, after joining MongoDB, I have spent 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 Americas, 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 overall go-to-market, how 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 3 theater leads who exceeded even that number in Q4 greatly from a net new business perspective, I have confidence in them.

Operator: Our next question comes from the line of Alex Zukin of Wolfe Search.

Aleksandr Zukin: 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.

Chirantan Desai: Yes. So Alex, I’ll touch on the first one. I — what I would like to say, so I was talking to a large financial institution in the U.K. 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 your help and your team’s help to make sure that for these 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, this 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 health care company, financial services or even government for that matter or health care. 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 build.

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 and Head of Transformation, but the opportunity still exists and it’s massive.

Michael Berry: Alex, thanks for the question. It’s something that we will certainly watch. What I’ll reiterate is we always do bundled 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.

Jess Lubert: Operator, we’ll take 2 more questions.

Operator: And our next question comes from the line of Tyler Radke.

Tyler Radke: 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 this sort of plans for new workloads? Just a higher bias on EA. And just curious like why do you think that customer, in particular, chose to do more on EA as opposed to Atlas?

Michael Berry: 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.

Chirantan Desai: Yes. 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.

Tyler Radke: Great. 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 on the database side, particularly for Mongo, the partner ecosystem, I think, has been tried, but certainly it’s 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?

Chirantan Desai: Yes. Tyler, absolutely, and I have been told what he just outlined. So I would put this in 3 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 2 or 3 of them to start with, and that is something that our teams are saying, we do need help as we think about this 2 or 3 system integrators. And make no mistake, the third bucket is also equally important is this AI native ecosystem that 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 3 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 on — and this is the inflection point.

Operator: And our last question comes from the line of Sanjit Singh of Morgan Stanley.

Sanjit Singh: So CJ, I wanted to just get your latest thoughts on a couple of topics. Given that the business has been accelerating, execution has been improving in the past several quarters. As we look forward, do we start 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 on 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 agentive momentum, not necessarily in the enterprise, still feel kind of consumer personal productivity. But just wanted to check your thoughts on the importance of the AI app story coming to fruition maybe a little bit earlier than maybe you anticipated?

Chirantan Desai: Yes. I would tell you it’s not if but when, okay? So right now, we do consider, I mean, Sanjit, 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, health care 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 productive 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. Mike, would you?

Sanjit Singh: 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 the — if you 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 application?

Michael Berry: Yes. Thanks for the question. So I think a couple of questions in there. One is, yes, Q4 largely came in as we expected, except for that small thing that we talked about. It was — 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, and that it is a consumption business. While we — 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 of years. And yes, those continue to perform as expected. As we’ve talked about 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.

Operator: This concludes the question-and-answer session. I’d like to turn it back to management for closing remarks.

Chirantan Desai: 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 and full year fiscal ’27 across Atlas and non-Atlas revenue, and we expect to continue expanding profitability while investing for growth all in line with our long-term financial model. Our results demonstrate MongoDB’s foundation is in great shape, and the company is well on its way to become the generational data platform of choice in the AI and multi-cloud era. Thank you very much for everyone joining, and we’ll see you soon.

Operator: Thank you for your participation in today’s conference. This does conclude the program. You may now disconnect.