MongoDB, Inc. (MDB) Earnings Call Transcript & Summary

Thanks for -- everybody for being here on the last day of the conference. And I know it's probably been an exhausting week for some folks. But we're really happy to have the MongoDB guys here, Michael Gordon, the Chief Operating Officer and Chief Financial Officer; and Serge Tanjga, who's the SVP of Finance and Investor Relations. And I don't know. He does a lot of different stuff. We were talking about earlier. I'm Jason Ader from William Blair. Before we get started, I'm required to inform you that a complete list of research disclosures or potential conflicts of interest is available on our website at williamblair.com.

With that out of the way, Michael and Serge, thanks for being with us.

Thanks for having us.

Great to be here.

Maybe I'd start out -- for investors who are not super familiar with the story. Can you give us a quick overview of the history, what you guys sell and who your customers are?

Yes, sure. So we at MongoDB, founded in 2007 initially as a modern database alternative. And so the database market, for those who don't know, because it's not there are tens of publicly traded companies in that area. Database is really what power every application, so it's one of the largest markets in all of software, and frankly, one of the most strategic. So if you think about the addressable market. IDC's numbers, I think, are now $85 billion in 2022, growing to $138 billion in 2026. So pretty significant growth as well. And really, what this reflects is the fact that the database is the heart of every application. And so if you think about all these cliches or phrases like software eating the world or every company becoming a technology company, really, what those are code for signal is that increasingly, companies are competing on the basis of their technology, which really means there's software. And that's not package software you buy off the shelf, because that obviously wouldn't provide any competitive advantage, but it's actually the software that you build. And all of those applications are built on a database, and we're the leading modern alternative, and we can talk all about the technical aspects if you want to, but just for like a broader audience, really, that dictates the speed, agility, scalability. So if you think about trying to compete for customers, innovate in market environments, COVID all of a suddenly changes your boots to large U.K. retailer and all of a sudden, you need to dramatically shift how you're approaching your consumer. That's all enabled and powered by having a nimble database at the core of your application. We have continued to extend the offering. We had our big annual user conference earlier this week. It's actually -- today is going on the third day of that. In New York, it was great to have everyone back in person where we sort of unveiled the broader developer data platform. Developers of the core audience, to your question about sort of the origin story or the history, it was really -- the company that's founded from the leaders, the CTO and Co-Founder, CTO -- CEO of DoubleClick, large internet ad serving. And what they kept running into is the scale of the number. First, hundreds of millions, then billions of ads that they had to serve a day. The relational legacy, databases just kept toppling over or crumbling down. And as they kept getting into solving the technology problems, they realized that the technology problems they were solving were all central to the database, and the database was the problem in terms of scaling. So ultimately, they went out and founded MongoDB to go build the database that they would want themselves as developers. And so we have over 35,000 customers. This is really a broad base. It's every industry, geography. One of the things that's different about MongoDB is the broad general purpose nature of what we do. So the breadth of use cases really runs the gamut. You've got large global 2000 Fortune 500 companies using MongoDB for core mission-critical applications. Large Wall Street trading firms using MongoDB and replacing their legacy relational technology. And using MongoDB, because MongoDB can scale more effectively. Utilities migrating their billing applications, so kind of core central systems of record and transaction environments in sort of the most demanding and often legacy environments, all the way to a modern upstart technologies and companies that have built the core of their business on MongoDB for the scalability, et cetera, et cetera. So a wide range of customers, broadly diversified. I don't know -- I'd stop there.

And then maybe, a minute on the numbers, where you are as a company right now.

Yes, sure. So we just reported our Q1 results last week. So generally, we've been able to demonstrate very strong growth. It was another quarter of strong growth. We did a little over -- what's the exact number of revenue?

$2.85 million.

$2.85 million, thank you. In Q1 revenue, that's 57% up year-over-year, very strong growth, a pretty significant scale. Our Atlas product, which is our Database as a Service offering, is now 60% of the overall revenue. That's growing 82% a year and we're seeing really strong demand for that across the board. We -- trying to think of other things. 78% gross margin on the subscription gross margin line of 75%. gross margin at the company level on a non-GAAP basis, excluding stock-based comp.

Your...

Operating income, positive for the first time on a non-GAAP basis in this quarter. We generated cash in this quarter. Last fiscal year, fiscal '22 was the first year, full year. We've had positive quarters before, but last year, was the first year that we were operating cash flow positive. So really seeing significant scale in the business, a significant growth given that scale, but just over 1% market share relative to the opportunity. So we do continue to invest in both sales and marketing and R&D. Obviously, scaling the rest of the business as well but have really strong underlying unit economics. You can shoot to see those through this kind of shine through in terms of the unit economics and the operating leverage that we're demonstrating and feel really good about where we are, but it feels early on in the opportunities set that we have.

Great. And you mentioned MongoDB World this week and the developer data platform. Maybe, just what are the key takeaways for investors from the user conference, from the investor session? And I guess you can maybe double-click on the developer data platform and what that means.

Sure. Yes. At the macro level, really everything that we talked about and introduced at MongoDB World earlier this week and that we highlighted or went through in some detail at the Investor Day, is all about making it easier to win more workloads. If you go back to that large addressable market that I was describing and the fact that we're just sort of early on in capturing it, we want to make it easier for people to -- make it easier for people to adopt MongoDB. One thing that's different for investors or maybe used to software or investing in software is typically the basis of competition for a software company is the customer, right? And you win the customer in total kind of lock stock and barrel, right? So if I'm the HR system for a company or if I'm the ERP for a company, that company only uses me, right? And they may talk about a land and expand model and that's -- I come up with my renewal if I'm the HR system, and I'm adding more seats, right, because my employee headcount has grown. And so they need -- I need more licenses and more seats for that business. The database market is a little bit different. As I mentioned at the beginning, every application has its own database. And so when you think about the opportunity set, that doesn't mean that suddenly, when we win a workload or when someone migrates off of Oracle, it doesn't mean that they kick Oracle out of the entire account. And all of a sudden now, every single application runs at MongoDB. And large enterprise will have thousands or tens of thousands of applications, right? So the basis of competition in our market is really sort of workload by workload. And so everything that we talked about at the conference -- at our user conference is geared towards making MongoDB easier to use and to win more workloads. So we really talked about kind of 3 types of things. We talked about making it even easier for additional use cases. Given the general purpose nature of what we can do, you can use MongoDB for a wide variety of use cases, where if a lot of people who sort of saw the challenges with legacy relational databases, built point solutions are sort of very niche solutions technologies. We instead have this broad-based general purpose database. And so what we did is we announced enhancements to Search, for application, Search. We announced enhancements to time series. All these things were things that people were doing before, but we just sort of made it even easier and more sort of customized or customizable for those types of use cases. We added products and technologies and capabilities around analytics, an in-app analytics. So that was sort of all in the scan of kind of different types of workloads or use cases. We also made a number of announcements around embracing modern technologies, right? So we put our serverless offering, which had been in preview into GA. That's not a dominant part of the market today, but it's more forward-looking. It's more how the developers of tomorrow who are coming up the ranks, who are in school today, they tend to think in increasing layers of abstraction, and so serverless is relevant for them. And also a bunch of stuff as it relates to mobile and edge computing. Again, sort of where the future is going. And then lastly, while migrating relation to legacy workloads has always been an important part of the story, we're continuing to try to make it easier and easier. And so we introduced a tool called Relational Migrator, which also help with that. And then in terms of the developer data platform, it's really about helping developers solve their challenges, and their biggest challenges are working with data. That's in terms of application creation and in a large general audience, I won't get into too much of the technical details, but working with MongoDB is dramatically more natural and intuitive for developer as opposed to trying to map back the data in a relational database, which is distributed across these tables of rows and columns which are not natural or intuitive to how they think developers today are mostly programming in, object-oriented programming languages, and our document model is directly compatible and analogous to that object. And so it's really about just extending different pieces of the puzzle. So whether it's Search, whether it's some of the analytics pieces and all that kind of stuff kind of represent the developer data platform.

So this is kind of like a -- almost like a marketing umbrella term, too? Is all the stuff that you've been working on for these past years?

Yes, I think, it's to help -- yes, sort of understand that it's more than a database. And I think it's sort of a descriptor for folks. It's what and how developers and our customers already think, right? This is not us sort of thinking in some sort of laboratory environment and concocting some new category to create some new gartner metric [ product ] or whatever. But it's really about the reacting to the customer pull and when -- as I described in origin story, like MongoDB is built by developers, for developers. And so we get a lot of feedback from developers about like what are the incremental challenges or what are the incremental problems that they face. Maybe Search is a good example. Most applications today have some sort of search, right? Your -- think of any of your consumer experiences you're trying to filter, that's effectively a Search capacity that you're looking for. Oftentimes, the way that work is the application will be built on MongoDB, which is straightforward and generally intuitive for a developer. But now, I also have to create a Search repository. So I have to send up a separate data store to manage the Search capabilities. Usually, that's based off of some open source technology called Lucene and there are a bunch of different flavors of what that looks like. And then I have to manage the sinking infrastructure in between the two to make sure that the application data is getting synced and replicated over to the search store. So now as a developer, I have to manage all 3 of those things. And so by introducing Search as part of this developer data platform, you can now remove all of that. You don't have to worry about that and you can just take care of it all within the context of the application.

Yes, I think that's a good segue to talk about just the macro environment and the value proposition of MongoDB is sort of the, I guess, elimination of a lot of different tools that maybe, people are using that address kind of niche use cases and workloads. Do you believe that, that's going to, I guess, rise to the 4 more as we move forward here?

Yes. I think it's a light tailwind from a macroeconomic perspective specifically, but I think it's more broadly a secular trend that we are seeing. I think people don't want to have more and more core infrastructure providers as companies build and innovate and introduce new applications, they don't want a net new database for every net new application that they build. They want to be able to standardize and increasing what we're seeing is that we become the modern alternative. And again, back to this, the lack of -- the fact that the business -- customers don't buy in the sort of monolithic behavior, you may have your legacy provider. But increasingly, MongoDB is getting sort of named or declared as sort of the modern standard that you build on going forward. So we hosted a customer panel as part of our user conference and as part of the Investor Day and had a number of different folks up there talking about how they were either migrating over and leaving relational or had already left and what those processes were like. And so that's sort of a behavior that we strive for, obviously.

And maybe, that's a good opportunity to talk about competitive landscape. How do you differentiate versus those kind of legacy relational? I don't want to get too technical, but maybe just a brief explanation of nonrelational versus relational. And then also, how do you compare against the cloud-native offerings from AWS, Azure, Google, et cetera?

Yes. I'll try and keep it at super high level. Maybe I'll go with my favorite analogy for nontechnical audiences, and I say this is a nontechnical person, is if you just think about the history of databases, relational databases were created 50-ish years ago. And the environment and the problem that they were trying to solve was that storage, right, the cost of a gigabyte of storage was exceptionally expensive. And so the solution -- the brilliant solution at the time of relational databases was to store things as efficiently as possible. And the result of that is that they distribute the data in this very complicated way. And the analogy that I often use is of a parking garage. And if you were the owner of the parking garage and you wanted to store as many cars as possible, when the car came in, you would disassemble the car, right? And you would put all the fenders in the fenders, and you put all the steering wheels in steering wheels and you would get many more cars into your garage. Unfortunately, in this analogy, where the parking garage is your application, the developer is the valet or the valet is the parking attendant, and they have to use the car. And now, they have to remember where is the -- car is parked. And that tax of that overhead for that developer, when they're trying to build the application is incredibly cumbersome and burdensome and also not very agile, right? So then you change. And our model is really called the document model. And the document model, obviously, today, storage is incredibly cheap and asymptotically going to nothing. And so the document model really just allows you to drive in your car and the developer to interact with car and not have to remember where it was parked and where the steering wheels and column C 32 and et cetera, et cetera, to sort of reassemble the car. So hopefully, that helps. But that's sort of the key difference. And what that leads to is significant ability to innovate more quickly, right? Developers are ultimately building user experiences and user-facing applications, revenue-generating applications for customers. That's sort of the basis of competition. And so when I strip away all of the sort of overhead or this tax of having to think about how do I map this distributed data back to my application, I can -- my developer productivity goes up dramatically. And for most companies today, that's one of their scarcest and most expensive resources. And so the developer productivity dramatically increases, which ultimately leads to their increased competitiveness.

And versus the cloud players?

Yes. And versus the cloud players, I'd say a couple of things. The cloud players, most of their business today is also relational, suffers from sort of the same challenges. They may offer a different licensing or other models relative to Oracle and some of the larger incumbents. But most of what the cloud players today is also relational. So all those advantages that I just described for MongoDB also hold. Google -- sorry, Microsoft and Azure, obviously, have seen the popularity of MongoDB and try to create invitation offerings. They're inferior, and when we're head-to-head, we win dramatically. But they certainly have much larger sales footprints and ecosystems than we do. And so one of the reasons why we continue to invest in sales and marketing in the way that we do is our footprint coverage is so thin, right? So our quota clearing headcount is measured in the hundreds versus the thousands or tens of thousands for our competitors. But from a technology standpoint, as long as we're in the conversation, we like ours odds quite a bit. I would say also, there's also an incredibly and increasingly strong partnering dynamic with the cloud players. I think early on, investors and others were sort of uncertain about what that dynamic would look like. I think over the last several years, you can see it certainly in our results, but also in the posture and tone of the way that they talk about things and the way that they behave in the market. And so we've increasingly seen that be more on the partnership side recognizing, of course, there's always [indiscernible] to that.

And can you talk about -- I don't know, just the database layer and how especially, your larger enterprise customers think about the database layer versus maybe some other elements of infrastructure in the cloud?

Yes. So databases are incredibly sticky. You can certainly see that in Oracle and other players, results and numbers. And so it's a vital part of the stack. I'd say the only thing that's maybe worth particularly calling out is there are significant customer concerns around vendor lock-in. I think that is generically true as it relates to public cloud, but it is particularly true as it relates to the database layer. I think people understand the strategic nature, the stickiness. And so there's a heightened degree of sensitivity. And so MongoDB runs multi-cloud, cross-cloud now so you could have a single application that's got multiple clusters and Google and Azure or GCP and AWS. And so that flexibility, in addition to the fact that you can run MongoDB on your laptop or on-prem or in a hybrid environment, I think, has a sense of sort of future-proofing it from customers' perspectives and not locking them into the database layer of the hyperscalers.

And the stickiness is a double-edged sword, though, right?

Yes, we talk about it in a sort of the sense of like, yes, we're -- it's hard to win workloads, right, because if there are applications that are working well, right? People are not going to change. But I think it goes back to this dynamic that we were talking about at the beginning, which is you never shut out of an account like there's sort of always opportunity, but some applications to your point, are absolutely sticky. So it's definitely a double-edged sword.

And then I wanted to ask you to talk about the nuances between your business model and say someone like a Snowflake?

Sure. Do you want to...

Yes, sure. So maybe just focus on us because we know that better. But when -- maybe specifically talk about Atlas. So Atlas is 60% of our revenue, our Database as a Service offering, and the revenue recognition model as well as how customers pay is based on consumption. So you pay as you go and you use -- as your usage grows, so you pay us more. And what's critically important to remember is that back to what Michael was talking about, is that on top of the database, it's the application. And as that application grows, so does the customer spend grows with us, and there, we're very well aligned. Customers build applications so that they get used. So as they see success and the application grows, they are happy to pay us more, and we remain reasonably well aligned with that. The opposite is not true. Meaning if the application was to decline and therefore, our spend with us declines, nobody is happy about that. because developer resources have been deployed, a tremendous amount of work and effort is gone into putting something that doesn't seem to have demand. So the fact that you're not paying for your database as much as -- it's not really particularly interesting. So what we see is that alignment that works reasonably well for us in that as applications grow, customers pay us more, and you see that in our numbers, in our performance because there's no third element to it. There's no -- like involvement of the customer in terms of how much they're paying because it's really the application that drives the consumption.

Yes. I think the only other thing that I would just add relative to -- it's not about other companies per se, but it's -- I do feel like people look for patterns, people try to sort of compare. I think to me, the key thing as it relates to consumption is consumption is a revenue recognition methodology. It's not a business model. And so just because someone has consumption rev rec doesn't mean that their business models are the same, whether their customer value proposition is the same or things like that. I think naturally, people try to look for patterns, right, experts of pattern recognition. But I think in this one, the consumption piece is really more the rev rec as opposed to like an underlying business model.

Right. And I think Dave talked about the data warehouse being tied more to sort of the amount of data you're putting into it, and that doesn't really necessarily a...

Yes. I think there's definitely business models where the pricing is focused on how much data am I adjusting or how much data I'm holding. And it seems perfectly reasonable to me that just because I'm hosting 50% more data, that doesn't mean I'm -- definition of like getting 50% more value, right? And I think this is some of the -- I feel like Splunk went through this a number of years ago. And so I think it's just -- people have to figure out what the right value proposition is.

We have about 5 minutes left. I want to give anyone in the audience an opportunity to ask a question. So if you got one, raise your hand. Otherwise, I'll keep going. On the macro side, maybe Mike will talk about kind of puts and takes as you think about the rest of the year. Maybe comment a little bit on your guidance for the year and what you saw in the prior quarter.

Sure. Yes. We -- what we tried to call out in last week's call is we have generally seen very strong environment for new business. New business ultimately turns out to be -- the primary driver in terms of winning new applications, is the primary driver of our results and our success over the medium to long term. In the shorter term because applications often start out small and [indiscernible] will grow, at least in terms of their sort of initial consumption. We also talk about the expansion of existing workloads. That tends to be a bigger driver of shorter-term performance. And so what we talked about was in the latter part of the quarter of Q1, particularly in the low end of the market. So our self-service channel and our mid-market direct channel, we saw slower expansion of customers, slower growth. So still growth, but not as robust as we've seen, particularly in Europe. And so we've mapped that back to macroeconomic activity because as Serge sort of described, the underlying usage of the database is driven by the end user activity in the applications. So if an application is having fewer transactions, I don't necessarily mean e-commerce transactions per se, but like any kind of transactions of the end user interacting with the application that not surprisingly, correlates to macroeconomic activity in general. And so we saw that, and it was only -- it was a very small factor in the context of Q1, about $2 million, but we wanted to call it out, help people understand. Our assumptions are -- I guess, maybe I'll quickly scroll forward to May. What we saw in May -- was -- we saw that self-service dynamic extend to the U.S. Europe didn't get any worse, still growing, but growing at a slower rate, but that did not deteriorate. But we did start to see it in the self-serve channel within the U.S. And so as we look forward from a guidance perspective, we felt that it was likely that, that would continue, likely that we would see that activity manifests itself in the U.S. in the mid-market. And given the macroeconomic underlying drivers of the behavior because we saw it kind of cross. And if you slice and dice Europe, we sort of cross regions, cross industries. It made sense that there wouldn't be some sort of macroeconomic firewall in between the mid-market and the enterprise just because we have a channel distinction. And so we assume there'd also be impacts in the enterprise channel to a lesser degree, because those applications tend to be more resilient and everything else. I think the only other thing is -- and so we factored that into our guidance, and we've quantified that for folks. And so that $2 million sort of compounds to about $5 million in Q2. And when you continue the kind of compounding of -- starting with a lower base and growing at a slightly lower rate and in addition to the broadening that I mentioned, that winds up being about $30 million to $35 million for the full year. So we sort of walked through and quantified all that. We continue to see very strong and robust wins and new logos. So the new logo environment and the new application environment continues to remain robust. We haven't seen any increases in churn or attrition or with an Atlas cluster deletion or like any of those kinds of things, which I think just sort of speaks to the stickiness and mission criticality of the underlying database. So those are kind of a quick set of highlights.

In the last minute, maybe just talk about the philosophy on growth versus profitability for the business, especially now as investors are really scrutinizing business models and profitability.

Sure, yes. So we've always had a long-term orientation, as I mentioned, just crossing 1% market share, incredibly strong product market fit, very robust unit economics. And so we've always taken a fairly balanced approach. Our view is that as investor -- I mean, as a management team and its kind of stewards of the business, our job is to maximize the long-term outcome. And so you see that showing up in the numbers. We mentioned to the first quarter of non-GAAP positive operating income. That was less an intention to react to current investor market. Part of -- at least my philosophy has always been, we'll never be able to react as quickly to how you all change or evolve your own thinking until we need some sort of independent sense for what makes sense for the company. And almost definition, that means we'll be a little bit mistimed or suboptimized for whatever the market is valuing most at a given point in time. But ultimately, we're here to maximize the long-term outcomes. And so continuing to invest given the big market, the strong product market fit and the really high returns you're getting, so it'll makes sense. And we've seen that sort of steady progression in our P&L, and we feel really good about it.

Excellent. Well, we'll close it off there. And thanks, everybody, for coming, and thank you guys for being here.

Thanks for having us.

And there's going to be a breakout upstairs in...