Why Anthropic, Meta, and Tesla All Chose the Same Database | Aaron Katz, ClickHouse

Summary

• ClickHouse entered venture formation with product-market evidence that most startups only earn later. Alexey Milovidov built it inside Yandex in 2009 for petabyte-scale streaming analytics, open-sourced it in 2016, and enterprises were already moving logging, metrics, and warehouse workloads onto it. In August 2021, Katz raised a $50 million seed/pre-seed with “no pitch deck…no product…no customers…and no revenue,” followed quickly by $250 million.
• Its commercial moat is as much distribution design as database performance. ClickHouse Cloud was built serverless with compute-storage separation for bursty workloads, then sold through self-service evaluation, free migration help, and engineer-to-engineer Slack channels intended to put customers in production “before our competitors have even scoped the project.” Katz now reports more than 3,000 cloud customers and hundreds added monthly.
• Katz sees AI adoption as SaaS history replaying at radically higher speed. Salesforce’s on-prem incumbents called cloud a fad; he expects objections to model reliability and enterprise data sharing to be debunked and says AI is being adopted “100 times faster” than SaaS was 20 years ago.
• The investor call is lower software multiples but durable infrastructure demand. Katz does not expect old forward-revenue valuations to return; free cash flow and terminal value now carry more weight, while databases remain “picks and shovels” purchased on price and performance once reliability, durability, security, and scalability are table stakes. He separates Datadog and Snowflake from application SaaS and cites Databricks at $4 billion of revenue, with warehousing and AI workloads each above $1 billion.
• Agents could become the buyers and operators of databases, not merely their recommendation layer. Claude recommended ClickHouse to Anthropic, a European fintech CEO said every LLM he queried did likewise, and Katz imagines agents provisioning ClickHouse plus Postgres automatically. Managed Postgres is in private preview, due for public beta in a few months and general availability by year-end; Katz says the unified stack will be “the world’s fastest Postgres service in the cloud.”
• Datadog faces interface disintermediation, but Katz thinks its near-term product moat is underestimated. Biewald argued agent users and easy custom UIs favor direct ClickHouse; Katz called the logic valid yet described Datadog as premium and formidable over a realistic one-to-three-year horizon. ClickHouse itself once spent seven figures on Datadog before earning revenue and faced an internal “mutiny” when migrating away.
• AI is expanding ClickHouse’s operating ambition without relaxing database-grade controls. Headcount is planned to rise from about 500 to nearly 1,000 this year, AI-assisted code contributions from an estimated 50% to 80% within six months, and agents are aimed at SDR- and CSM-like work. Human review stays because “move fast and break things doesn’t apply to a database.”
• The smooth external trajectory conceals concentrated execution risks. The core team moved from Moscow to Amsterdam six weeks before Russia’s February 24, 2022 invasion. Katz later says he believed $200 million was custodied at U.S. Bank while $100 million was on SVB’s balance sheet; he pulled the $100 million 30 minutes before SVB’s system went down, while the remaining $200 million stayed uncertain for 72 hours. Reliability is P0, and well-capitalized warehouse and observability incumbents are “waking up to the threat.”

Deep dive

Not yet available upstream; scheduled sync will retry.