ClickHouse, Inc., a leader in real-time analytics, data warehousing, observability and AI/ML, announced it has raised $350 million in Series C funding. The funding round was led by Khosla Ventures, with participation from BOND, IVP, Battery Ventures and Bessemer Venture Partners as new investors, and existing investors including Index Ventures, Lightspeed, GIC, Benchmark, Coatue, FirstMark and Nebius. This round follows previous investments of over $300 million, bringing total funding to over $650 million.
This combined funding will be used to scale product development, support global expansion, and deepen partnerships with customers and technology providers to enable the next wave of AI-powered applications. In addition to this funding, ClickHouse also secured a $100 million credit facility led by Stifel and Goldman Sachs.
ClickHouse’s momentum is accelerating, having grown over 300% in the past year and now serving over 2,000 customers across industries ranging from fintech and transportation to consumer and healthcare. New customers include Anthropic, Tesla and Argentina’s Mercado Libre. They join companies like Sony, Meta, Memorial Sloan Kettering, Lyft and Instacart, as well as AI innovators Sierra, Poolside, Weights & Bases, Langchain and many more.
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Today’s announcement came during ClickHouse’s inaugural user conference, which demonstrated how enterprises are building data products to meet the demands of the agentic era.
“With AI agents taking hold in data-driven applications, observability, data infrastructure and beyond, the demand for agent-centric databases like ClickHouse has reached an inflection point. The future of analytics is much more than dashboards. It’s intelligent agents that interpret data, trigger workflows and support decisions in real time,” said Aaron Katz, CEO of ClickHouse. “But AI is just one driver. We designed and built ClickHouse from day one to support a broad spectrum of real-time data applications across industries, and our momentum reflects the eagerness of enterprises for a platform that can keep pace with their scale-up ambitions.”
“We invested in ClickHouse because they solve one of the most critical infrastructure problems of the AI and agent era: enabling real-time data platforms that can support both traditional analytics and the increasing demands of AI-driven workloads,” said Ethan Choi, Partner at Khosla Ventures. “As AI reshapes every industry, the ability to deliver fast, scalable, and efficient analytics is becoming fundamental. ClickHouse is well on its way to becoming the default engine for next-generation intelligent data products.”
The Next Frontier: Real-Time Analytics for Agentic Workloads
ClickHouse’s market traction is rooted in a fundamental shift: Enterprises are no longer just building dashboards or batch reports — they are building real-time, intelligent data platforms that must serve both human and AI agents. Because AI agents can generate queries much faster and with higher frequency than human analysts, agent-centric databases must support low-latency, interactive analytical queries with increasingly high throughput.
ClickHouse was designed from the ground up to meet this demand. Its high-performance, columnar storage engine powers interactive, analytical queries across massive data sets with minimal latency — perfect for AI and ML applications, real-time analytics, cloud storage, and observability workloads.
Built for speed at scale: High-performance analytics across industries
Traditional databases and storage systems struggle to meet this demand. Transactional databases don’t scale for analytics workloads. Meanwhile, traditional data storage systems are optimized for internal, batch-heavy use cases that suffer from limited competitiveness and slow performance. Finally, query-centric technologies are becoming prohibitively expensive for structured analytics — requiring 10x more storage and processing power, and limiting the practical scope of applications due to their associated costs.
In contrast, ClickHouse offers a purpose-built solution that bridges this gap by combining high-performance analytics with the scalability and competitiveness that today’s intelligent, data-driven applications demand.
Source: BusinessWire