ClickHouse Clicks With $350 Million Series C Round

<p><strong>SAN FRANCISCO<&sol;strong> &&num;8212&semi; ClickHouse&comma; Inc&period;&comma; a provider of real-time analytics&comma; data warehousing&comma; observability&comma; and AI&sol;ML&comma; has raised &dollar;350 million in Series C financing&period; The round was led by Khosla Ventures&comma; with participation from new investors BOND&comma; IVP&comma; Battery Ventures&comma; and Bessemer Venture Partners&comma; as well as existing investors including Index Ventures&comma; Lightspeed&comma; GIC&comma; Benchmark&comma; Coatue&comma; FirstMark&comma; and Nebius&period; The company now has raised total funding of over &dollar;650 million&period;<&sol;p>&NewLine;<p>&lbrack;<strong>Photo above<&sol;strong>&colon;  ClickHouse Founders &&num;8211&semi; Aaron Katz&comma; Yury Izrailevsky&comma; Alexey Milovidov&rsqb;<&sol;p>&NewLine;<p>This combined funding will be used to scale product development&comma; support global expansion&comma; and deepen partnerships with customers and technology providers building the next wave of AI-native applications&period; In addition to this financing&comma; ClickHouse has secured a &dollar;100 million credit facility led by Stifel and Goldman Sachs&period;<&sol;p>&NewLine;<p>The company reports that it grew over 300&percnt; during the past year and now serves over 2&comma;000 customers across a range of industries from fintech and transportation to consumer and healthcare&period; New customers include Anthropic&comma; Tesla&comma; and Argentina’s Mercado Libre&comma; among others&period; They join companies such as Sony&comma; Meta&comma; Memorial Sloan Kettering&comma; Lyft&comma; and Instacart&comma; as well as AI innovators Sierra&comma; Poolside&comma; Weights &amp&semi; Bases&comma; Langchain&comma; and more&period;<&sol;p>&NewLine;<p>&OpenCurlyDoubleQuote;As AI agents proliferate across data-driven applications&comma; observability&comma; data infrastructure&comma; and beyond&comma; the demand for agent-facing databases like ClickHouse has reached an inflection point&period; The future of analytics isn’t just dashboards&period; It’s intelligent agents that interpret data&comma; trigger workflows&comma; and power real-time decisions&comma;” said Aaron Katz&comma; CEO of ClickHouse&period; &OpenCurlyDoubleQuote;But AI is just one driver&period; We designed and built ClickHouse from day one to support a broad spectrum of real-time data applications across industries&comma; and our momentum reflects that enterprises are hungry for a platform that can keep up with their scaling ambitions&period;”<&sol;p>&NewLine;<p>&OpenCurlyDoubleQuote;We invested in ClickHouse because they’re solving one of the most important infrastructure challenges of this era of AI and agents&colon; enabling real-time data platforms that can support both traditional analytics and the growing demands of AI-native workloads&comma;” said Ethan Choi&comma; Partner at Khosla Ventures&period; &OpenCurlyDoubleQuote;As AI reshapes every industry&comma; the ability to deliver fast&comma; scalable&comma; and cost-efficient analytics is becoming foundational&comma; ClickHouse is poised to become the default engine for next-generation intelligent data products&period;”<&sol;p>&NewLine;<p>The market traction around ClickHouse is rooted in a fundamental shift&colon; enterprises are no longer just building dashboards or batch reports—they are building real-time&comma; intelligent data platforms that must serve both human and AI agents&period; Since AI agents can generate queries much faster and at a higher rate than human analysts&comma; agent-facing databases must support low-latency&comma; interactive analytical queries at an increasingly high throughput&period;<&sol;p>&NewLine;<p>ClickHouse was designed from the ground up to meet this demand&period; Its high-performance&comma; columnar storage engine enables interactive&comma; analytical queries across massive datasets with minimal latency—perfect for powering AI and ML applications&comma; real-time analytics&comma; cloud data warehousing&comma; and observability workloads&period;<&sol;p>&NewLine;

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