Companies that use ClickHouse

Source: Analysis of Linkedin bios of 192 companies that use ClickHouse Enterprise

I noticed that ClickHouse Enterprise customers tend to operate in data-intensive, real-time decision environments. These aren't just tech companies. They're financial services firms executing trades at microsecond speeds, logistics platforms routing millions of deliveries, cybersecurity companies analyzing threat patterns across vast networks, and fintech businesses processing payment transactions. What unites them is the need to make immediate sense of massive data volumes. They're building platforms where seconds matter: fraud detection systems, algorithmic trading infrastructure, customer conversation platforms handling millions of interactions, and supply chain optimization tools.

These are predominantly growth-stage companies that have achieved product-market fit and are scaling aggressively. The funding stages cluster around Series A through Series D, with typical raises between $25M and $200M. Many employ between 200 and 1,000 people. I also spotted several Fortune 500 enterprises and post-IPO companies, suggesting ClickHouse scales from high-growth startups to massive organizations. The employee counts and funding amounts signal companies managing serious data volumes but still hungry for competitive advantage.

Source: Analysis of tech stacks from 192 companies that use ClickHouse Enterprise

I noticed that companies using ClickHouse are typically fast-growing, data-intensive organizations that prioritize operational excellence and team efficiency. The presence of tools like Slack Enterprise Grid and Golinks suggests these are scaling companies with distributed teams that need sophisticated internal infrastructure. They're not just collecting data, they're building their businesses around real-time analytics and making data accessibility a core competency.

The pairing of ClickHouse with Statsig is particularly revealing. These companies are running extensive experimentation programs and need the analytical horsepower to process feature flags and A/B test results at scale. Similarly, the correlation with ElevenLabs Enterprise suggests they're early adopters of emerging technologies, willing to integrate cutting-edge AI capabilities into their products. The combination of ZipHQ for procurement and Golinks for internal knowledge management tells me these organizations are obsessive about removing friction from their operations, even in seemingly mundane areas like expense management and link sharing.

My analysis shows these are product-led companies in their growth stage, likely Series B and beyond. They've achieved product-market fit and are now scaling rapidly, which explains the need for Enterprise Grid rather than standard Slack and the investment in tools like Eightfold for talent management. They're dealing with hiring challenges that come with hypergrowth. The tech stack suggests engineering-driven cultures where data informs every decision, from product features to hiring to resource allocation.