ClickHouse raises $400M as AI companies including Anthropic, OpenAI, and Tesla use it for real-time analytics

fakes of Elon Musk as the farmer from Babe Pig in the City uh looking at the slop and being sad. So fun day on the timeline. Good that there will be some changes coming. Anyway, without further ado, we have Aaron Catz from Click House. Welcome to the stream. Thank you so much for hopping on the show. Good to meet you. How's your year going so far?

Well, the calendar year is behind us, but our fiscal year is about to finish the end of this month and it's going really well. We got, you know, whatever, eight or nine days left and, you know, we're off to a off to a good start to finish the year and the fiscal quarter and get the new year uh up and running beginning of February.

What's the theme of 2026 for the company? Is it just more AI? It feels like AI is so obvious, but also you you what else are you going to focus on?

Well, you know, Clickhouse has been a back-end database to a lot of agentic workflows over the past couple years, even before the chat GPT moment. You know, we're being used by lovable, cursor, anthropic, open AI. Pretty much every leading AI company right now is using Cluck House in some sort of capacity. So, but that's just not AI companies. I mean, we're the back into technologies like ramp, for example. You're a sponsor if you talk to Eric. Uh we power most of the analytical experiences if you're a a RAMP customer. And so, it's just kind of doubling down on what's gotten us here. uh it's a very large surface area that we're going after and um just kind of broadening the competitive landscape.

Have there been any challenges on uh on actually scaling the business from an infrastructure size? You're at a scale where uh many AI companies are struggling with data centers GPU poor. Uh how has the actual build versus buy decision changed over the last few years? How is the how has the infrastructure side of the business changed? Yeah. Well, scalability is one of Clickhouse's strengths and always has been. I mean, we've got, you just talked about Elon's. Many of Elon's c companies are using uh Click House. Tesla's a great example of that where they're ingesting a billion events per second into ClickHose and there just isn't another database in the world.

Not using Click House. So,

yeah, just tell us who's not a customer and then it'll be quicker.

Yeah, fair enough. I mean, you just kind of get your head around the volume of data that these LLMs are generating and the ability to ingest that in an efficient way to be able to store and analyze that, you know, ClickHose really shines. So, scalability is something that we we really promote and our customers talk about as one of the unique characteristics of ClickHose.

Yeah. Um, how are you thinking about uh just walking through the ladder of different analytic suites and analytic functions and and just case studies that can actually uh that are best practice today? I mean, people are familiar with, you know, like big data, map reduce, you know, count a bunch of things across a bunch of databases. Uh, we're in a much more modern era. What are you seeing companies do that's unique, surprising, interesting, or uniquely enabled by Click House? Yeah, you mentioned map produce or any sort of kind of batch oriented processing, it's all moving towards real time and ramp is a great example of that. If you're a user or customer of ramp and you want to run analytics on spend patterns inside of your company, you're not going to wait, you know, two to 5 seconds for that dashboard to render or that graph to update or the report to produce results. You expect to see those in milliseconds. And so there's just this broad shift from an analytical perspective to real time experiences. You batch processing, you know, even waiting, you know, 3 to 5 seconds for any sort of dashboard to refresh is just an eternity. And so that's a big pull to why people are moving towards clicks.

You're Oh, sorry, Jord.

Yeah, I wanted I wanted to ask about the engineering culture. Last week we were at a dinner and somebody was telling me about I don't I I'm I'll I'll kind of mix up some of the details but they were telling me about like the an investor was going through the diligence process with click house and click you guys had shared like that uh that they couldn't believe how like how few engineers had created some of the early technology and they just honestly didn't believe it. So I wanted to ask about kind of the early engineering culture and and how that's evolved and and and uh what you guys are doing on the talent side that has allowed you to you know work with so many in uh of these you know massive important companies.

I mean I I love that question and I don't get it often enough. the engineering team at Clickhouse, the broader community behind Clickhouse, but the creators and the committers that are part of our company are the best engineers that I've ever worked with. And I've been in the industry for quite some time. I know you've had Mark Beni off on your show several times. I spent 12 years at Salesforce and had an incredible engineering culture. Um, the team that we've assembled here is specifically in infrastructure software is the best in the world. And you're right, it was a very small team of primarily Russian engineers inside of a company called Yandex. Um,

which was commonly referred to as the Google of Russia that actually created Click House originally. My co-founder, Alexe Milivid, who lives in Amsterdam, is the one that actually named it. It's short for Clickstream Data Warehouse. And so, he was thinking about the data warehouse use case when he created the database itself and then made the brave decision to open source it in 2016. And that's essentially you just expose your source code to the world and then anybody can adopt and deploy the technology with no attribution to the creators of the software without any sort of commercial relationship. And it was a small team. It was a dozen engineers uh who were the primary committers that created this incredibly powerful featurerich uh database. And it's a total joy to work with this group. They're all in Holland in the Netherlands uh now all part of our company and continue to advance the project. And then we've built a managed service that runs in the cloud called Click House Cloud uh that they're also contributing to. Um and that's the primary business model. And this is a managed service that runs on Amazon, Google and Microsoft infrastructure. And then in Asia and primarily in China, we have a partnership with Alibaba. H how are you thinking about the way that developers and teams are selecting database backends, data storage products in the age of agentic coding? I feel like we talked to a lot of folks who uh they go to an agentic coding solution. They say I want to build this type of application. and I want to build, you know, some custom piece of software and the database choice is sort of made for them by the by the coding agent and and this feels like it's hyper relevant at the vibe coding the the DIY hack project level, but is this something on your radar where you think that in a few years, maybe it's already happening, um how you show up in LLM search results and how how the uh AI agent coding models feel about Clickhouse will be important to your business.

Well, you know, Anthropic uh spoke at our event uh last year in San Francisco. So did OpenAI and Tesla and Anthropic discovered Clickhouse by asking Claude what they should be using for observability and Claude said you should be using Click House. And I had a had a call with the CEO of a very large fintech company in Europe last week. And he said, "Every LLM we ask what we should be using for this new real-time analytics product we're building suggest Click House." And so, you know, fortunately, a lot of people are turning to these LLMs for guidance on what technologies they should be uh they should be adopting. And I think as everybody knows like you know it decision-m has been completely turned on its head from kind of a tops down seale mandate you're going to use Oracle you're going to use IBM now to a developer uh evaluation and open- source creates such a fast path for a developer who's building an agentic application to deploy experience experiment with technology without any sort of vendor relationship they can actually push it in to production for some of these agentic applications without any sort of vendor relationship. Open source is completely disrupting you know how these uh LLM providers and enterprises are deploying these applications and we made an acquisition last uh week that we announced on Friday alongside our financing that we're super excited about. It's a company out of Berlin called Langfuse and they have built you know an industryleading LLM observability application so that now enterprises can observe you know the types of experiences their users are developing on these LLM uh applications.

Very cool. How are how are you processing uh all the chaos in SAS right now the selloff broadly the industry's transition you know uh uh you know went through uh you know couple decades where

a big question about the shift from seats to consumption or or performance results

yeah there's so many there's so many I feel like open questions how much of a threat are are new uh you know you you probably laugh when people say like oh I made this database with a prompt and you're Well, you're missing like, you know, the hundred other features that, you know, an enterprise is really going to care about. But after spending, you know, more than a decade at Salesforce and then running Click House, I'm curious what your point of view is.

Yeah, I you know, John mentioned this move from a seatbased model to consumption or usage based, which infrastructure isn't that unique. I mean, it's been around for quite some time. like our customers simply pay for what they use which is a combination typically of storage and compute and these are very kind of AI intensive applications and what's unique about our service is that it automatically scales up and down so you don't need to provision all of the compute that you otherwise would because a lot of these analytical workloads are quite kind of spiky in nature and you want the application to be able to idle during periods of inactivity for example and so I do think that you know these traditional seat based although I think we should separate like traditional business applications like Salesforce and workday from kind of infrastructure software which is much more of kind of the plumbing of you know the internet and the stuff that you don't see necessarily when you look at a mobile app or you look at a a business app or consumer app it's a lot of the processing that occurs you know behind the scenes is primarily where we exist I'll give you an example is you know we where I would historically use some sort BI reporting to build a graph or a chart to show me how the business is performing. You know, build me a bar chart that shows revenue growth or build me a a stack bar chart that shows regional revenue distribution, things like that. And I'd go to some data analyst and they'd go and find the source data and they'd spend a week pulling this together and we'd have like multiple reviews. I now simply ask Anthropics. We've integrated Anthropics, you know, cloud, I think it's 4.5, their latest model with our own MCP server and then a click house cloud service that has all of our customers prod not not our customers data but like our customers use of our service and I can ask that uh I can ask that prompt like build me a bar chart that shows these dimensions and it builds it in like 5 seconds and it's just and it cost me 20 cents uh that single prompt and that simple semantic search is generating like dozens of SQL queries. All of those SQL queries are all being stored in click house. And if you think about the characteristics of these uh agentic experiences like the number one requirement is latency. They have to be low latency in terms of the interactivity between the text prompt where you whether it's chat GPT or anything else where you put in that query and then the database itself that's actually storing the data that's providing the response.

Yeah. Uh it's it's fascinating how much of a global company Click House is the Alibaba partnership, the Russia history with Yandex. Uh we were reading a post about selling software in Japan and how the Japan software buyer often will want to read a lot of documentation and details before jumping on a call with a sales associate. Uh does that match with your reality in Japan? what what can you tell us about the difference of buyer across different uh different countries that you've experienced throughout your career? Like what's the key to global growth uh broadly?

Yeah, it's a great question. I mean, so you know, half of our employees are outside of the United States. We employ people in 22 different countries. Half of our customers are outside of North America. Half of our revenue comes from outside of the US. So the company is extremely diverse uh internationally. I had the good fortune in 2005 so 21 years ago Mark Beni off asked me to move to Singapore and I spent four years helping Salesforce expand across the Asia-Pacific region. And at the time Japan I believe was the second largest country behind the US ahead of the UK, Germany, France in terms of revenue contribution. Not I I don't think I could be quoted on that because I'm not necessarily true. It was number two or three, but it was like top five. And I would argue it was probably top two if my memory serves me correctly. And you could add South Korea to that same description of just how unique these markets operate. Um, and how localized the selling effort is. We recently did and I I've seen both models and one being you do a joint venture and where you partner with a local company and you share the risk and you share the economics and you share the upside and they leverage local relationships in the market and local market knowledge etc. or you try to do it yourselves and establish your own KK in Japan. And I' I've gone down both paths and and learned a lot of lessons along the way. And so here at Click House, we did a joint venture in Japan. We recently announced that with a firm called Japan Cloud and they were previously Sunbridge which is the firm that did Salesforce.com's joint venture and so worked with these folks for you know two decades now and so yeah it's a highly localized market um the buying behavior is very different in Japan and in South Korea than other parts of Southeast Asia uh putting aside greater China um or Australia New Zealand or the Indian subcontinent. So, it's a huge market. Um, but not many companies get it right, honestly. You know, they try to do it themselves versus leveraging local expertise. We also brought on some investors, a firm called Geodessic Capital, and that's run by an individual named John Roose. And John, I believe he's still on the board of Salesforce, but he was the previous ambassador for the United States to Japan. And just having those types of relationships are very important for a company like ours that we frankly don't have the same level of awareness in Japan that we do here in Silicon Valley or, you know, in New York.

Mhm. Yeah. Makes a difference.

Makes a lot of sense.

Fascinating. Uh Jordan, anything else?

Yeah. Very cool. Thank you.

We'll let you get back to your day. Thank you so much for the show.

At this rate, I'm I'm sure there'll be many reasons to

We have to ring the gong there. The uh there's a recent fund raise. Can you tell us the details?

Yeah, happy to. you know, we we weren't running a process or raising capital. There's a lot of investor interest and so we ended up pulling around together uh kind of over the holidays that was led by Dragon Ear uh here in San Francisco. Um and uh we ended up raising 400 million. We had participation from a number of our existing investors and a few new investors. Incredible. So pulled together over the holiday. We've talked to a lot of VCs who said that it was easier to do deals over the holidays. there were less distractions at the office and so plenty of time to hop on the phone with like a tight partnership, get something through. So congratulations.

Love it. All right. Well, I appreciate it. Thanks for having me on.

Yeah, we'll talk to you soon. Have a