MongoDB, Inc. (NASDAQ:MDB) Citi’s 2024 Global TMT Conference September 4, 2024 3:50 PM ET
Company Participants
Serge Tanjga – Finance and IR
Michael Gordon – COO and CFO
Conference Call Participants
Tyler Radke – Co-head and senior software analyst at Citi
Tyler Radke
Looks like we had a packed house here for MongoDB. So thanks for joining. Tyler Radke here, co-head of the software sector at Citi. I think this is session eleven of a busy day, so appreciate it. MongoDB. Joining me we have Michael Gordon, the CEO, sorry, COO and CFO.
Michael Gordon
Maybe one day.
Tyler Radke
Not spreading any rumors here. And we got Serge Tanjga, from finance and investor relations. So gentlemen, thank you for joining the conference. This is probably the 6th year in a row I think you’ve come, so very much appreciate it. Just for investors that maybe have a little bit less familiarity of Mongo, just give a quick overview of who Mongo is and in the context of the database market, where you play, how is GenAI play into where you’re going?
Question-and-Answer Session
A – Michael Gordon
Yes, sure. First of all, thanks for having us. Great to be here, as always. Had a bunch of great meetings. Thank you all for coming. For those who don’t know, MongoDB developer data platform, the leading modern general purpose database. We play in one of the largest markets in all of software, 80 plus billion according to IDC, and shockingly still growing at double digits. Normally you tend to think about markets that are a little bit more mature, maybe growing more in line with GDP. One of the reasons why the database market is growing so quickly is because it’s so strategic, so fundamentally at the core of how companies drive competitive advantage. You hear phrases like software eating the world or every company becoming a technology company. Those are shorthand phrases for companies using technology to drive their competitive advantage. That comes from internally built software. Obviously, you can go buy off the shelf software, but everyone else can buy it.
So that doesn’t provide any competitive advantage. So you have to go build your own software, drive competitive advantage so you have to go build your own software to drive competitive advantage, whether it’s for internal applications or externally facing ones. And at the heart of each one of those applications is the database. And MongoDB, as the leading modern general purpose database, is what provides the agility, the scalability, and solves a number of the problems that exist from some of the legacy relational alternatives. We can get into that in more detail. I won’t go into a slew of that right now. That’s really how we’ve come along with this better mousetrap and been able to have a lot of success closing in on $2 billion in revenue from ten years ago, having very little, obviously the last, now almost seven years as a public company, you’ve sort of seen that growth in our ability to separate from the rest of the crowd.
Not surprisingly, large markets that haven’t been disrupted or disintermediated in decades should draw capital. And MongoDB was one of those companies that was sort of founded to tackle this opportunity. But the reason that we’ve been successful when others haven’t, and why we’ve broken out from the pack, and the one who’s achieved real critical mass is the technology really is excellent and a better mousetrap.
Two, we’ve very successfully earned the trust and won the hearts and minds of developers, developers the ones who are building the applications. Then third, we’ve paired that with good execution in order to capitalize on opportunity. And that sort of general purpose nature of what we do has allowed us to gain, share and really excel.
So the GenAI portion of the question, I really say when we look at the impact that AI, and specifically Generative AI, will have on the industry, on the market, and on MongoDB specifically, I call out three main areas where we see that opportunity. The first is it generally with code assist tools and other things, should allow developers to be more productive. So that means more applications will be created. So this very large market already of, like I said, 80 plus billion growing at double digits, should grow as a potential to grow even faster with GenAI. There are different estimates out there, and I think it’s still a little bit too early to tell what people talk about. 10%, 25% 30% improvements in productivity. When those companies talk about those productivity gains, they don’t talk about cutting their number of developers, they talk about executing more of their product roadmap. There’s a lot of stuff that is high value, that doesn’t get built just because of capacity constraints. That’ll mean more applications get built, we should benefit from that in terms of the overall market growth.
The second way that we think that we have the opportunity to benefit is more of those applications will be modern applications, right will be applications that benefit from our database, from the flexibility and scalability of a MongoDB. And so that presents a market share opportunity for us. And then the third bucket is the vast majority of that 80 plus billion dollars today is in legacy relational technology. And people have talked about and want to move portions of that to MongoDB. But re-platforming is hard, right? It takes a lot of work, takes a lot of effort. Generative AI can accelerate that process.
In addition, a lot of organizations data is trapped in legacy systems. And so the ability to harness and capture some of that proprietary data that can make generative AI differentiated and powerful for you as a business. And so that presents sort of a third opportunity for us. So why don’t I stop there and kind of dig into any and all?
Tyler Radke
No, that’s great framing and nice way to kind of break up the different ways that it impacts you. I thought it sort of weaves that in with sort of the recent trends in the business because Q1 was obviously a tough start to the year. You took down the full year guide, you talked about weaker consumption, yet we’re still in this environment where there’s a lot of interest and signs of spending on AI. So clearly you’re not seeing the tailwinds yet from what you just laid out.
Can you just walk us through sort of what happened in Q1, what elements got better in Q2, and then how do you sort of think about the timing of some of these ultimate GenAI tailwinds?
Michael Gordon
Yes, let me try and tackle all that. Maybe I’ll take a little bit of a step back. Just when we talk about the macro environment, there are a couple of different ways that it can affect businesses. And why don’t we talk about, or I’ll talk about how we see it potentially affecting us. And the two main ways are ability to win new business and the impact on existing workloads that we’ve already won. And so if you think about the impact on new business, we’ve had a very strong track record and a lot of success winning new business in all environments. Now, to your point, Q1 was a bit of an off quarter for us, particularly as it relates to new business. As we speculated or said on the call in, I guess it would have been the end of May call, we didn’t think that was a result of the macro environment. That was really more internal issues, operational issues, sort of our own organizational piece, and that we got started operationally to the year with a slow start.
That’s things like rolling out comp plans, territories, things like that. We were a couple of weeks behind where we normally would be because it was our first year of dealing with some of the workload data that we had. But in Q2, we had success despite the current macroeconomic environment, and we were able to win new business. So I think pretty consistently and I’m going to kind of look at Q1 as kind of a one-off. In all economic environments, we’ve been able to execute successfully.
A lot of times when we talk about macro, I worry just in listening to all of you and trying to process it all, when you hear other companies talk about macro, they usually are referring to new business. They’re talking about sales cycles, elongating deals, slipping deals, requiring higher approvals, things like that. We’ve been able to navigate all of that. Part of that, like I said, is strong execution. Part of that is we’re a really small share player in a really big market. We ought to be, I think about it mentally as a visual of the ocean. The waves at the top can be choppy, but if you’re a small, small, low percent share player at the bottom, like you shouldn’t really be affected by any of that turbulence up on top.
That’s a new business side as it relates to macro. And so I think we’ve been successful in executing really in all environments there. Where we have been really affected in macro is with the growth of existing workloads. So our relationship, our underlying usage, which translates into consumption, is very closely tied to the end user activity. So the underlying reads and writes in the data database. And because we’re a general purpose database, because the customer base is very diversified now, over 50,000 customers, we have all sorts of applications, all sorts of use cases. The underlying activity mirrors economic activity now, not necessarily in a way where I can map to you the coefficient for labor force participation and CPI and GDP or whatever, but we clearly see slower underlying growth in times of slower or worse macroeconomic conditions. That’s where we’ve called out how we have been macro affected, and we’ve seen that. We continue to see that, and that’s incorporated in our guidance.
The other thing to the Q1 piece that we called out was that the workloads that we’d won in fiscal 2024 were exhibiting slower growth characteristics than what we would have expected. Part of that is a result of every year we make sales compensation changes, and we’ve been on this sort of multi-year journey to reducing friction. And we took another step in that in fiscal 2024, which reduced the incentives or eliminated the incentives for upfront commitments. And so as a result, we end up having some unintended consequences whereby sales reps were focusing on winning new volume of workloads, but without necessarily fully appreciating or qualifying for their growth potential. And so as those fiscal 2024 cohorts are growing at a slower rate than we expected, that was part of what we called out and observed in Q1 and updated our guidance.
In terms of GenAI, there’s a lot of excitement, there’s a lot of activity, there’s a fair amount of experimentation. But I think we were one of the early ones that’s cautioned about what was the timetable that it would take before it translated into inference into production workloads and would show up at the transactional operational layer. There’s a lot of money being spent on chips and testing and other things, and obviously you don’t have to look forward to know where those dollars are going, but they weren’t really matriculating into everyday workloads. We talked to customers who are experimenting with things but have a couple of workloads in production or a bunch of tests that they’re running but not yet really running at inference or production scale.
So I think that will happen. It will take time. I don’t think that will materially impact for us fiscal 2025, but more and more as people continue to work through that, we will see those workloads moving through. But again, I tend to think about it more as a three or five year time horizon rather than saying what’s going to happen next quarter.
Tyler Radke
Right. Okay, and then going back to 2Q where you did see certainly a much better beat and raise. I think you talked about the new business growth, new workload acquisition improving and then consumption tracking slightly, slightly higher, but maybe not materially higher to sort of alter.
Michael Gordon
I think that’s right. Q2, healthy on new business sort of confirming the kind of Q1 blip or internal footfall to whatever you want to describe it as. And yes, importantly, in terms of the consumption trends in Q2 within Atlas, they were a little better than what we had expected that contributed to albeit in Q2 and also is part of the explanation for the raise for the full year that we had in the call last week.
And I think that’s, to your point, kind of within the normal range of outcomes. It wasn’t such a huge beat that would cause us to either point to specific workloads because at this point we’re pretty diversified or some specific underlying change in the macroeconomic environment. We’ve talked about how in Q1 of this year we saw the week-over-week growth in consumption beverage slower than a year ago.
And that was true in Q2 as well. It was slightly slower than it was last year. And so I don’t think there’s anything to suggest that the macroeconomic environment is materially better, worse, obviously happy to outperform and see that flow through, but not in some sort of way that I would indicate was any kind of material change.
Tyler Radke
Right. And as you think about the consumption piece, which you sort of attribute to macro, arguably, that’s the least out of your control out of everything. What gives you confidence that this isn’t just kind of the new normal? I know you have some great charts at analyst day showing that macro impact, but do you see any signals or anything that gives you confidence that we can sort of return to a higher level of underlying consumption than we’ve seen in the last two years?
Michael Gordon
Yes. So a couple of key things that I think through in sort of trying to like sort through that dynamic. The first is in the chart that you’re talking about basically just shows, if you have existing workloads, if you’re snapshot and freeze frame things. Right.
You have existing workloads. Existing workloads continue to grow, but they grow at a slower rate. And so if you didn’t add any new workloads, over time, your growth rate would naturally slow.
Right. And so really the, when you think about how do you accelerate your growth rate, it really all depends on what are your assumptions about how many new workloads you can win and they’re impacting the growth rate or what happens to the growth rate of the installed base. To your point, the growth rate of the installed base tends to be more out of our control.
Right. And so the things we focus on are the things that are within our control, which is how many new workloads can we win? How quickly can we win them to the conversation earlier? What’s their growth potential and how do we make sure that our salespeople are focusing on the best workloads? Things like that.
Tyler Radke
Right, right. Okay.
Michael Gordon
I think the other thing that I’d add just for folks who follow the stock, this will be familiar for those who don’t. We also talked about just if you think about like the reported numbers. Right. And kind of the year-over-year numbers from a growth rate standpoint. In the March call where we gave the fiscal 2025 guide, we called out roughly about $80 plus million of kind of one time headwinds that are affecting this year’s growth rate.
About half of that is from multiyear deals on enterprise advance, the EA product and the 606 accounting consequence with that, we had a particularly strong EA year in fiscal 2024. And then the second piece is this chunk, about $40 million as well from unused Atlas commitments.
As we’ve moved to reduce friction, we’ve de-emphasize the sales force, selling these upfront commitments. Most of the time someone uses a commitment, but occasionally they don’t. And when they don’t, it’s a user or lose a commitment.
So that benefits the bottom line. So we kind of moved away from that. And so I think just also mathematically, when you’re looking at growth rates and everything else, it helps to understand those are a headwind and a tough compare in the current period that obviously will lap come next year.
Tyler Radke
Yes, one of the, I think this probably the biggest upside surprise, at least to investors last quarter, was the guide for Q3, which suggested some of your strongest sequential growth that you’ve guided for in a while. You also raised the full year by more than you beat in the quarter, implying strength in the pipeline. How would you sort of efficate [ph] that increase in guidance between the Atlas piece, which probably benefited a bit from better than expected consumption, better new workload growth versus EA, just based off of what you’re seeing in the second half.
Serge Tanjga
Yes, so I’ll take that. Those are the two pieces, but let’s take them in turn. So what we said on Atlas and what Michael also just talked about is that consumption in Q2 was modestly better than we expected, which means that exit ARR for the rest of the year. So exiting Q2 and into Q3 is higher than we would have expected. And so it was modestly better. We’re very happy about that. The starting point is higher, but not sufficiently so that we change our consumption assumptions for the rest of the year. So consumption in Q3 and consumption in Q4 are really unchanged compared to 90 days ago. However, you do have this higher starting base that you kind of benefit from for the rest of the year. So we basically just flew that forward when it comes to our guidance. And that’s an element of the raise in the back half of the year.
And then the other element of the raise is that we are feeling a bit better about the EA pipeline for the back half of the year. It’s not a dramatic change and it’s not concentrated in any particular industry or geography. It’s just as we get closer to renewing some of those deals because most of our EA businesses, renewal and upsell, we’re just seeing incremental upside in terms of more workloads that we can sell, more incremental capacity that we can sell. And that’s beneficial not only because it’s better ARR, but also in the case of EA, you get to see that revenue sooner because you get to recognize the term license component immediately. So those are sort of the two pieces that it comes out to and those combined make up for the increased guide. But it’s a bit of both. Sometimes the investors think it’s only EA, or maybe it’s predominantly Atlas, but kind of both are relatively important to explain that raise.
The only other thing that I would say, because it’s come up, people are asking about sort of the implied fourth quarter guide and sort of, and if you do the numbers, roughly 10% growth implied in the guidance in the fourth quarter. A few things to keep in mind, to kind of wrap your head around that number. First is Michael was talking about these onetime items that we’re facing. They are particularly relevant, or at least some of them are in Q4. So our unused commitment year-over-year headwind is actually highest in Q4 because that is the highest renewal quarter. So although $40 million is somewhat evenly spread throughout the year, it’s actually the biggest chunk is in Q4. So as you think about year-over-year, that’s a portion of it. That’s also the second highest multi-year comp after the Q2 that we’ve just been through. So you got to keep that in mind.
And then the final thing, which is maybe a touch more complicated but worth going through, Michael mentioned that consumption was weaker. Consumption growth was weaker in Q1 of this year versus Q1 of last year. Slightly weaker in Q2 of this year versus Q2 of last year, we are forecasting it to again be weaker year-over-year in Q3 and Q4. And as you think about how consumption flows into year-over-year growth rates, we do expect Atlas reported year-over-year growth rate to continue decelerating. And that’s also part of what would drive the Q4 guide.
Tyler Radke
Okay, great. And appreciate the explanation on Q4. So we got that question a lot. So maybe if we think about some of the new products and some of the announcements that you’ve had over the last year on GenAI, you’ve rolled out vector database, you’ve rolled out stream processing. I think there’s been some other new capabilities that were announced at .local this year. Where are we at just in terms of the maturity of those products? And are you expecting them to be starting to move the needle by the second half this year? Is this more of an FY 2026 story? Just talk us through the impact of those new products.
Michael Gordon
Sure. Yes. For those who follow or pay attention to the product announcements or attend our various .local events, there’s a very ambitious product roadmap, which is great to see. I do think it’s important to underscore, as exciting as all the new opportunities are, the core is the OLTP transactional operational database that we continue to invest in and push forward with. And we kind of previewed the data [ph] release that we’re very excited about. That’s the core of things.
Search has probably been the most established and kind of pre-positioned us for vector, and so that’s certainly been going well. If I think about things more broadly, partly because the way we charge and partly because the way customers buy all these things are close to related. The goal is really to win more new workloads, and we can have a lot of really interesting intellectual discussion around. To what do you attribute this workload? Did you win this workload specifically because you had vector search? Did you win this workload specifically because you have stream processing? Some of that is very intellectually stimulating, but also wildly imprecise.
And the key thing is really about making sure that we’ve got ultimately the developer data platform, but including the core operational database that people want to build applications on. It’s particularly well attuned to modern applications. As we were talking about earlier, I do think that search and vector search are sort of most proximate or most adjacent or most relevant for the highest percentage of workloads. It’s very early on in stream processing, but we’ve gotten a lot of compliments about the ease of use and the seamless integration. But I don’t think of these things as things that are game changers in the short term, but more in the.
If you look out three to five years and you say, okay, what would the MongoDB outcomes have been without these products? It will look better as a result of having made these investments, not just for the very few of these have actual SKU level line items that we’re charging for, but because it should allow us to continue to maintain developer preference, continue to win a higher percentage of new applications and new workloads. And then there’s obviously the whole relational migration world, which is a little bit different, but hopefully that kind of sets it up.
Tyler Radke
Yes, that’s helpful. And I actually did want to hit on relational migrator. And I think for Mongo since IPO, clearly there’s this massive opportunity of sort of like locked up spend in these, these legacy SQL databases. But I’d say it’s been a market that you’ve slowly chipped away at. But I think about a quarter of the business roughly over time has come from relational migrations. As you think about this relational migrator product, which I think you’ve had a couple iterations of, and there’s some more features that are GA, like how significant of an accelerant in that legacy relational opportunity do you think this could be? As you think about all the AI enabled products, do you think this one could maybe move the needle the most?
Michael Gordon
Yes, it’s interesting. I think there’s a big opportunity, but I think it will take time. Right. We tried to balance our own internal enthusiasm with the reality of when it will affect the P&L or the forecast or the numbers. But to your point, relational has always been part of the MongoDB opportunity. I do think that a lot of people have a somewhat artificial construct of this idea of relational NoSQL, right, which I think is partly sort of invented because relational was the dominant legacy technology. We and others came along with an alternative. Industry analysts Ed Gartner and IDC in other places need to have some way to describe it. And so that sort of comes up and you get the sense that there’s this sort of like you’re either one or the other. And right, to me that’s part of where the MongoDB positioning is as general purpose and broad base is helpful to cut across that. But so we’ve been able to win workloads, win migrations from relational to your point.
Now, it doesn’t happen easily, and it only happens when a customer is experiencing a high level of pain with their relational application. They’re experiencing downtime, they can’t scale, they’re having problems because moving is hard and it takes time and it takes money. One of the things that’s exciting though, to your point about generative AI is it has the opportunity to shrink that amount of time to reduce the cost and the complexity of migrating, which therefore means that applications that you want to move but maybe aren’t experienced so much pain that you justify the cost now have to clear kind of a lower hurdle and there’s sort of more opportunity to migrate things. I do think that it will take time. None of this is sort of an auto magical just press a button, sit back, and suddenly your relational application is working among a DB.
In the early pilots that we’ve done, it’s like on Zoom and you accidentally do something in fireworks or whatever. In the early pilots we’ve had a lot of success, but it’s early. There’s a healthy human component, but they’ve been able to leverage the technology to show real proof of value in relatively short periods of time. The goal over time is to have more and more of a technology component or quotient in that proportion, in that relationship. I think we’ll always have some human in it though. But the more and more that we can shrink that down, which are still early days in, I think that will be an even bigger and bigger portion of the opportunity set right.
Tyler Radke
As we think about sort of the new applications being built, particularly this hopefully wave of GenAI enabled applications which you alluded to earlier. This could be a big accelerant to the overall database market, but very early to tell. You’ve talked about having 1000, I think, AI customers already today. I guess what are the signals or the metrics that you’re looking at that gives you confidence that you’re sort of winning the lion’s share of those workloads? There’s obviously a number of competitive vector databases out there. Postgres has been at least talked a lot about by investors. So what of gives you the confidence that your market share in GenAI is at least as good as in the cloud and mobile type of applications.
Serge Tanjga
Yes, so it’s early days, so it’s difficult to quantify. What we take particular comfort from though, is the feedback, the unsolicited feedback that we’re getting from both customers and partners. Where it begins and ends is actually at the database. And so customers understand that building true value add AI applications will require bringing a proprietary, disparate data to the LLM or the AM model that they’re using. And that would require more flexibility and more throughput and more scalability than most other databases can provide. In fact, all of them, but particularly relational.
And so what’s interesting is that the foundational sort of technical advantage of this company is a document model. And now we have customers coming to us and partners coming to us to say, yes, I can see why document model is the best data solve, because I can solve with all my data in a single place. I can avoid multiple systems and silos and streaming or ETL ing data. And that’s why I customer want to build on top of MongoDB, or that’s why I partner, want to partner with MongoDB, because I see you as the winner and you’re part of the AI stack. And that’s sort of the important part.
Goes back to what Michael was saying. It is early days, it’s mostly still proof-of-concepts where we’re seeing customers having success both at the startup side of the market and increasingly, although still rarely at the enterprise size of the market builds our conviction that at that database layer, our right to win is particularly strong.
Tyler Radke
Got it. Then on the partnership side with the hyperscalers, clearly the hyperscalers have seen probably the most momentum from an AI monetization. Granted, a lot of that could be training in GPU costs that we see in their numbers. Part of the narrative that we hear talking to IT executives is this notion around consolidation. If I’m going to be deploying Microsoft OpenAI service, maybe it makes sense to leverage some of their database capabilities as well, or other data management capabilities. Can you speak to that dynamic? What have you seen on the hyperscaler fund? And how do you sort of make sure that you’re still in that strategic position, even if customers are doing more directly with the hyperscalers?
Michael Gordon
Yes, I would say that the fundamental relationship with the hyperscalers is unchanged. So on the competitive side, some form of bundling has always been their strategy. So, hi mister customer, you’re buying infrastructure from us, so why wouldn’t you look at all these other services, including databases, and you’re not necessarily looking for the best-in-class, but or some subset of use cases, it’s probably good enough. Obviously they’ve had success, and particularly AWS have built a large database business as a result. But bundling has always been sort of the key element of differentiation versus our approaches. Best in class technology developer, developer affinity and platform independence.
But now you fast forward to the world of AI, and is that really different? Or in other words, is their ability to bundle somehow better than it used to be? And what we’re hearing from customers is that they’re very obviously, they’re interested to experiment with AI and are facing sort of world level pressure to figure out what their AI strategy is. But at the same time, they’re hesitant to sort of put their chips on the board too soon for a number of reasons.
Number one, you don’t want to pick a winner too early, because it is actually very early in the days of AI. And students of enterprise technology know that the winner in month 15 isn’t always the winner in month 60 or month 120, and we are very early on. Second is expenses. A lot of those solutions are proprietary and therefore more expensive. And in some cases, at least, that’s the reason that proof-of-concept doesn’t become a production app, because the question about ROI is not there.
And then finally it hardens lock in. Large enterprises are aware the more business they give to any particular vendor, the more power the vendor has against them. And so that’s sort of a reason to not put all your chips on the table with really any provider. And then I guess to come at it at a different angle. And you started actually with the concept of partnership. Our partnerships overall have never been stronger with the hyperscalers, and we only see them going from strength to strength, which would be surprising if at the same time they were more successful taking database business for us. I think they see us as an important, highly popular technology that they want to partner with closely, and AI doesn’t change that.
Serge Tanjga
Yes, I think another interesting customer dynamic that we’ve seen is customers coming to us saying, what do you think we should do? Because we know that if we go talk to a hyperscaler, we know what their solution is going to be.
It’s going to be whatever’s in their stack, as opposed to, can you help us figure out this opportunity, what we need to do, what makes sense, things like that, which is part of the reason why we created this map program, to assemble the right resources and skills and partnerships to help customers build AI applications more quickly.
Tyler Radke
Yes, got it. So talking about the direct sales force in your go-to-market team, I think at the second half of last year you did sort of increase investments, at least on the quota carrying side. Can you talk about just so your aspirations in terms of how fast you want to grow your sales force? Obviously, we’ve heard in the past how Dave has talked about you’re under resourced, the win rates are good, but it’s the deals that you’re not in that, I guess keeps them up at night. Where are we at in terms of building that out? And how do you just think about the balance of investing versus showing leverage?
Michael Gordon
A few different thoughts there. One, it’s a balance of continuing to extend footprint coverage, continuing to increase productivity, and continuing to make progress from a profitability and a margin standpoint. And so let me sort of walk through each of those.
In terms of the footprint coverage, we still have relatively small footprint compared to our opportunity and compared to our competitors. And so that makes sense to continue to invest in. There’s enormous amount of opportunity that we don’t see. And while our win rates are very high in the deals that we’re in, there’s plenty of activity away from us. And that is concerning. And so it makes sense to continue to invest in that. And we’ve done that. We’ll continue to do that.
Secondly, we’re continuing to increase productivity. We talked about on the call about how we increase productivity year-over-year. It’s not always a perfectly straight line, but when we think about efficiency in the go-to-market, an enormous amount. And so that’s a focus area.
And then the third piece to your point is absolutely sort of this balancing, whether you want to call it growth and profitability, or however you want to think about it, I do think it’s also important not just from a pure profitability standpoint to understand that there are genuine operational constraints to how quickly you can grow. If you think about an individual sales rep, I can only hire so many new people on my team and be effectively ramping a certain number of people and make sure the quality of their ramp is successful so that once they ramp, they’re producing at appropriate and attractive levels. And so while there are clearly financial considerations, there are also operational considerations when you figure out how fast and how quickly you can grow that out. But certainly we want to keep building, building out that capacity.
Tyler Radke
Great. One of the elements of the database market that’s been very important over time is the idea of pricing. Just given your strong renewal rates in database market. Obviously there’s maybe companies, the large players in the space that have abused pricing and angered some customers. But how do you think about pricing? I know that in the past you’ve done some price increases on EA and list prices. Is that something you’re looking at this year? How do you just overall think about your pricing power?
Michael Gordon
Yes. So on year, you’re correct. We’ve done a number of pricing increase, although it’s been a few years. Frankly, mostly in the early days of my close tenure where we felt like we were particularly underpriced compared to the market. But we know that leverage there. We think that some of our customers who are coming in for multi-year EA deals are coming for that reason to lock in pricing. And every time another competitor raises prices, it may result somebody else to be like, well, I just want to make sure I’m on firm ground with MongoDB, so let me do a three year deal as opposed to a one year deal.
On Atlas, historically we haven’t raised prices. You can make a solid argument that we could. Generally though, our posture is that that would be the wrong thing to do in the context of where we are in gaining market share. There are deep scars in this market from companies raising prices consistently and to the customers that trim in. We are primarily in the volume game at 2% share, so we don’t want to do anything to send wrong signals or trigger bad memories from the past. We are here to win workloads and to the extent that the pricing is a leverage there, but not one that we’re necessarily looking to pull in the near term here?
Tyler Radke
Got it, got it. Makes sense. And then as we think about the top of funnel trends, you continue to see pretty healthy customer additions. Obviously the MongoDB historically has been synonymous with open source. I know you made some more protective changes to the licensing with SSPL in years past, but what are some of the things that you’re doing as a company to ensure that you still get that leading edge developer mind share? And what are some of the metrics that you track beyond just downloads to the community version or customer editions to ensure that that’s healthy?
Michael Gordon
So it’s actually super important. And we are a company built by developers for developers and our product spends vast majority of that time thinking about what does developer want today? How is their workflow changing? Where can we find incremental data problems to solve this? To stay front and center, but everything from our dull local series, which I forget now, but something closer to 30 cities in the world where we’re organizing developer events. Just yesterday we had one in Seoul to looking at top of funnel metrics even before what you see. So what are the registrations on the Atlas website? How big is our free tier? Are customers getting value from the free tier and they’re regularly graduating into becoming a paying customers? Downloads are also another way to get it. So we are deeply sensitive to remaining front and center and never want to take that affinity for granted. And a lot of what we do revolves around education, along with DB University as well. So those are all examples of ways that we should continue investing to make sure we remain front and center and we’re very sensitive to it.
Tyler Radke
Great. Maybe in the minute and a half that we have left, I’d love just to turn it over to you if there’s anything we didn’t hit on that you wanted to cover or just sort of what the message is for this well attended session.
Michael Gordon
Yes, so a couple of things. I think in general we hit on all the key topics. The 101s have been a bunch of questions about the quarter in the guide and all that kind of stuff. But I think if you take a step back and think about the long-term trends, for me it’s all sort of been captured in the fact that we have this very big market, we have relatively small share. For those who don’t know, it’s probably important to understand the market is not just fragmented in terms of the providers, the competitive set, but it’s a market that buys workload by workload.
And that’s a little bit different. If you’re selling HR software and you’re an HRS company, you go into Citi and Citi picks you, they get rid of everything else. The sales and trading side doesn’t run on the different HR platform than research. When Citi picks MongoDB for one application, it’s just one of thousands. There’s a workload by workload dynamic that I think is different than most in software and not everyone understands and appreciates and that’s part of why the opportunity, but also the changes and some of these trends play out over multiyear cycles.
And so I think that’s, to me, maybe the key thing to keep in mind, and what gives us sort of enthusiasm over a multiyear cycle is that we’ve had this ability to grow and kind of grow at above average rates. We weren’t happy with Q1, and we’d said publicly that we think that’s not our natural rate of growth. And so we look at all the sort of possible legs of growth for the future. I think we’re quite excited. So why don’t I just leave it there? But…
Tyler Radke
Great.
Michael Gordon
Thanks for having us.
Tyler Radke
Yes. Appreciate you joining and thanks the audience for the great turnout.
Michael Gordon
Thanks, Tyler.
