The Exchanges

Q What was your biggest lesson from working with him? If there was one takeaway?

A That you can overestimate what you can achieve in one year and underestimate what you can achieve in five. When I started, it was a three-year-old startup, and it was basically a glorified contact manager, you know, Salesforce automation. Um, we essentially said what you're traditionally using ACT or Goldmine or using a spreadsheet, you can use Salesforce for. But Mark had this bigger vision and he said, we're going after Siebel, SAP, Oracle, Microsoft. We didn't have the product set to go after those competitors, but he was such an incredible marketer that he created this perception in the industry that some of the largest companies in the world could adopt this technology and that we would deliver on a roadmap that would satisfy the requirements over time. And he did.

AI assessment note: “That you can overestimate what you can achieve in one year and underestimate”

Q Why football? Why English Premier League? You can sponsor F-One, you can sponsor, you know, LaGuardia Golf as well. Why football?

A Well, I love the sport, but let's put that to the side for a minute. I think the value of these sponsorships obviously come in two forms. The first is awareness. And as we saw last night against Chelsea, this is a game that's being televised globally. So you've got millions of viewers that are looking at your brand and you're getting impressions, obviously. The second, which is obviously easier to quantify, is hospitality. And we're sitting here at Craven Cottage along the Thames. I think this is arguably the best sports experience in the world, and I've been to many. We had 20 executives last night attend an intimate Michelin grade dinner. We had, you know, the C-level executive come from Paris, one of the largest banks in Europe, just to experience that. And those types of relationships are extremely important, especially as we move up market.

AI assessment note: “I think the value of these sponsorships obviously come in two forms.”

Q they're about tenders. We see them more and more for employees, and I think talent acquisition is one of the hardest things today. I actually got in a lot of trouble the other day for this. I said, if you are trying to hire A-star talent today, you can't. OpenAI and Anthropics simply pay, and they go to the front-end model providers. Is that true, or was I being glib?

A I think it's true depending on the category that you're in. I think if you're a Digital native AI startup in San Francisco. It's a very difficult employment environment because you're competing against OpenAI and Anthropic and others, um, that are extremely well capitalized and are putting offers that are extraordinarily aggressive into the market. I think if you're a infrastructure provider like ClickHouse, uh, we look for a slightly different, um, profile. You know, we're looking for database engineers, people that have experience with distributed systems. Um, slightly different than what the frontier labs are hiring for. We employ people in 27 different countries, um, which gives us a competitive advantage, so I can hire engineers in Portugal and Germany and Singapore. Um, you know, we've got single digit attrition, so we've got extraordinarily high retention. Um, we have done some structured secondaries, um, and we'll continue to do so over time, but not with the frequency that I think some of the younger companies are doing.

AI assessment note: “I think it's true depending on the category that you're in.”

Q If you could have your way, would you not have everyone be in office in some way?

A I, I wouldn't, and I'll explain why. Uh, we're a very international company, uh, by almost every measure. Over half of our revenue comes from outside of the US. 40% here in EMEA, 10% in Asia. Over half of our customers are outside of North America. And so we need to support our customers in a variety of different languages, in a variety of different time zones. I mentioned we're live in 36 different regions around the world across all three hyperscalers. There's no way that you can centrally manage that. From one location. You need to have people in every single time zone. You need to have relationships with the hyperscalers in region. We go to market with AWS. We go to market with Google Cloud. We go to market with Azure. I flew to China to launch a partnership with Alibaba. Like you're going to have, you're going to need local language speakers to maintain those partnerships. And you can't do it from one or two or three centralized hubs.

AI assessment note: “I, I wouldn't, and I'll explain why.”

Q So I am, you know, Controversial in many ways. Uh, one of them is because of my vocal, uh, expressions about remote work. Why am I wrong?

A I don't think you're missing anything. I'm of two minds and I contradict myself constantly about this topic because I spent 12 years at Salesforce. I was in the office every single day, five, six days a week, 10:12 hours a day. And it was during this extremely formidable time in my career. I learned so much. From those experiences being in the office amongst my colleagues and peers, learning from people with more experience than I do, than I had at the time. When I started this company, it was during COVID, and so we kind of had to be distributed by design, and I started it with some Europeans, and so people were in Europe, I was in the Bay Area, my co-founder was in Utah, and so, you know, we started the company, we grew very quickly, we Found engineers that had a very unique skill set and they weren't all in the Bay Area. They weren't all in London. They weren't all in New York. And so we built a distributed company. Fast forward to where we are today. We're almost 800 employees. We'll be a thousand by the end of the year. We are introducing, uh, in-person options for our employees. We don't have this draconian return to work mandate or return to the office mandate, but we do have offices and we have a huge office in Amsterdam. We have an office here in London, New York. The Bay Area.

AI assessment note: “I don't think you're missing anything. I'm of two minds”

Q How do you think, Nikesh at Palo Alto is a very good friend of mine, he's a very brilliant M&A. How do you think about the buy versus build versus distraction? What's that internal decision maker for you when you think about those six acquisitions?

A If I think that our product and engineering teams can innovate in a specific area that we're not in today, then I'll let that play out organically. If I see a founder or a group of founders that are building on top of ClickHouse, that are getting into a category that I think is going to be You know, a future component of what we build as an ultimate data platform. Then I think about doing something inorganically and we partnered again with six different founders, uh, actually more than that. Some of these companies have multiple founders. Our most recent one earlier this year was Langfuse out of Berlin, um, which is three incredible founders entering agent observability. Every enterprise in the world is going to need this technology.

AI assessment note: “If I think that our product and engineering teams can innovate... I'll let that play out organically.”

Q Am I glib and wrong, and that won't take into account infrastructure plays, or is that actually just the new world that we're in?

A Well, as I mentioned previously, I think the durability of revenue is the most Underestimated attribute of these companies, meaning how high are the switching costs when somebody's using your product? And for any category that goes from zero to a hundred million in a year, I worry what's the competitive moat that they have to preserve that hundred million from that customer going to something else. So ours was a bit more gradual. We went 12, 5200, and we'll finish this year north of 500. Which in the database world is faster growth than we've ever seen, including all of the competitive companies that I mentioned earlier today in terms of the first three years of revenue growth. And it's over a very broad customer base. So we've got very little concentration risk. The basket of AI companies that's using us in nearly every AI companies built on ClickHouse from Harvey, Sierra, Decagon, Anthropic, OpenAI, et cetera, represents less than 12% of revenue. And so even if half of that goes away, the winners are going to offset the loss from the losers.

AI assessment note: “durability of revenue is the most Underestimated attribute of these companies”

Q You said there about, I love this, the AI awakening. The challenge then becomes, and we had the president of Uber on the show, who was much more skeptical of the ROI that it generated internally. Um, how do you, do you think about token budgeting cost when suddenly you're incentivizing this, hey, run free, and then the bill might come at the end of the quarter?

A Well, the primary measure that we care about, as you know, is revenue growth. And if we see The sustained revenue growth that we've experienced over the last three years, and we're a very efficient company, as you know, um, some would argue we're too efficient. Then I worry less about the expense that we're incurring on coding agents, for example, because we're covering a very broad surface area and our roadmap is accelerating at a pace that we've never seen before. And as long as we can continue to ship features that satisfy this very broad set of use cases, Then I can always rein in token consumption and the cost of tokens, as we know, is going down, not up. And so they're becoming more efficient, not less efficient, but our revenue is growing faster than it ever has. So I'll take that trade any day of the week.

AI assessment note: “I worry less about the expense that we're incurring on coding agents”

Q You said that you're too efficient in some people's eyes. Where should you have spent where you didn't spend? And how do you reflect on that?

A So we've got about a hundred quota caring salespeople, for example, and I think, you know, our revenue scale is significantly more than a hundred million. And so our average, uh, rep productivity is quite high relative to the industry average. Our competitors that we're going up against some of these very large data warehousing companies, some of these very large observability companies have thousands of salespeople. They wake up every morning thinking about one specific use case. Our salespeople wake up every morning thinking about 10 different use cases. And there's only a hundred of them going up against an army of 2003 thousand sellers for some of these very large data warehousing companies. So I think the one thing, and if I look back over the last two years that I wish I had done differently was increasing sales capacity.

AI assessment note: “I wish I had done differently was increasing sales capacity.”

Q Do you think you raised aggressively enough? We're seeing a new world by capital. It's more and more moat in a lot of cases.

A You know, I'm trying to build a generational company that outlives me. And I think right now a lot of people look at fundraising As a very short term exercise, and they want to have this consistent and steady step up in valuation. It's good for your employees. You give them liquidity through tender offers. It's good for recruiting. It minimizes dilution. It bolsters your balance sheet. Uh, it lets you forward invest. All of those things are true, but I'm thinking about a company 20 years from now, not two years from now. So whether or not we raise that fifteen billion or twenty five billion in 10 years is irrelevant. Right? We need to have the right investors involved. We need to build a very durable, long-lasting, sustainable company. We need to get to a billion dollars of ARR as quickly as possible. The most important metric for the company is new customer acquisition. We add hundreds every month. Our gross retention is north of 99%. Our net dollar retention is north of 200%. The addressable market we're going after is absolutely enormous. So I think less about valuations perhaps than I should.

AI assessment note: “whether or not we raise that fifteen billion or twenty five billion in 10 years is irrelevant”

Q I do want to weird transition back, but when we said about kind of agent preferences and agent, you know, Anthropik using Anthropik to choose ClickHouse, does that mean like developer relations, developer community becomes less important? And how does the future of brand change when agents become decision makers?

A So I talked about you're building an application, like that you're building a dating app, right? So you can build it over the weekend. You can vibe code it, right? And in theory, that agent can select the stack, right? It can select a managed Postgres service because you want to support transactions. It can a managed ClickHouse service because you've got analytics, uh, and everything in between. You still have an enterprise buyer. You still have a huge data warehousing project at a top bank or a telco that's going to be driven by an engineer or a developer. And there's still going to be a human that's making that architectural decision on, are they going to use ClickHouse? Are they going to use Snowflake? Are they going to use Databricks? You've got an observability workload. Are they going to use something off the shelf like Splunk or Datadog? Or are they going to embrace open source and use something like ClickHouse? Those, for the next decade, there will still be a human involved in that decision loop.

AI assessment note: “there will still be a human involved in that decision loop”

Q Can I ask how much do you spend on that topic?

A A significant amount. You know, I, we weren't doing enough at the turn of the calendar year, so I sent an email to the company, and the subject was the AI awakening, and I said, I think we're moving too slowly, and I'm not seeing the adoption of these, uh, coding applications, for example, that I would expect to see for a leading database provider like ClickHouse. And the company rallied, uh, to the call, and we've seen just this explosive growth In terms of our use of these, of these applications. Um, and we're now looking at adopting more open weights models for us, just the traditional frontier labs, but I think Anthropic specifically and open AI have the benefit of being both a model provider and the harness provider that the open weights models right now are behind in.

AI assessment note: “A significant amount. You know, I, we weren't doing enough”

Q process, trust and security are so important. Everyone is saying that we're at this golden age in terms of cybersecurity, and we see more and more security hacks. How do you feel about the security vulnerabilities that come with the agentic future that you are planning for in three years out? More on the enterprise side. We obviously see it on the personal side, but more on the enterprise side.

A Well, I think it's going to require multiple deployment models. So you need to be able to consume services via a cloud offering through any one of the three major hyperscalers. You're going to need the ability to manage that data on-prem behind your VPC in your firewall. So you're going to need to have the flexibility to deploy these applications as you best see fit, especially in the end in the enterprise. Where you've got highly regulated industries, a lot of data privacy concerns, a lot of compliance requirements. And so as a supplier to these customers, we think about how do we support them dependent on their deployment preference? And, you know, that's a tricky roadmap to maintain because most companies pick one of those avenues. You know, I mentioned Snowflake and Datadog. They're primarily cloud services. You know, you look at more traditional technologies that run on prem. And so if you force your customer into a specific lane, you know, you're limiting the addressable market that you can go after.

AI assessment note: “I think it's going to require multiple deployment models.”