News
Key Takeaways
- ClickHouse raises $400M to drive expansion and innovation.
- ClickHouse Langfuse to add LLM observability for AI applications.
- Enterprise data teams gain integrated analytics, transactions and AI observability capabilities.
ClickHouse on Jan. 16, 2026, announced a $400 million Series D funding round led by Dragoneer Investment Group. Bessemer Venture Partners, GIC, Index Ventures, Khosla Ventures, Lightspeed Venture Partners, T. Rowe Price Associates and WCM Investment Management also participated.
The company also revealed its acquisition of Langfuse, an open-source LLM observability platform, and launched a native Postgres service built in partnership with Ubicloud. According to company officials, ClickHouse Cloud now serves more than 3,000 customers with annual recurring revenue growing more than 250% year over year.
Recent customers include Capital One, Lovable, Decagon, Polymarket and Airwallex, joining an existing base that includes Meta, Cursor, Sony and Tesla.
Table of Contents
- What ClickHouse Added — and Why It Matters
- The Strategic Moves That Led to ClickHouse's $400M Round
- Why Enterprise Data Stacks Are Collapsing Into Platforms
- ClickHouse at a Glance
What ClickHouse Added — and Why It Matters
The announcements expand ClickHouse's platform across multiple areas:
| Platform Expansion | What It Enables |
|---|---|
| Langfuse acquisition | Adds open-source LLM observability with 20K+ GitHub stars and 26M+ monthly SDK installs |
| Native Postgres service | Ubicloud partnership delivers unified transactional and analytical workloads |
| Data lake support | Expanded compatibility with Apache Iceberg, Delta Lake and data catalogs |
| Postgres-ClickHouse sync | Company claims up to 100X faster analytics via native CDC and NVMe storage |
| Full-text search | Enhanced capabilities for observability use cases |
The Langfuse acquisition allows ClickHouse to serve teams building applications powered by large language models. As enterprises scale their LLM deployments, observability becomes critical for monitoring performance, costs and model behavior.
The Strategic Moves That Led to ClickHouse's $400M Round
ClickHouse laid groundwork throughout 2025 with strategic product and financial moves. In January, ClickHouse Cloud added HIPAA support in compliant AWS and GCP regions. By July, the platform introduced SharedCatalog and stateless compute, enabling faster spin-ups across native and open formats like Iceberg and Delta Lake. Three months later, the company extended its Series C financing with new investors, including Citi Ventures and Insight Partners.
The company also broadened its international footprint in late 2025. In November, it established ClickHouse K.K. through a partnership with Japan Cloud to target the Japanese market. Days later, it announced a direct integration with Microsoft OneLake, enabling native querying of data stored in Microsoft Fabric.
Why Enterprise Data Stacks Are Collapsing Into Platforms
Enterprise data infrastructure is consolidating fast as organizations race to move AI from pilots to production at scale. The market is shifting toward unified platforms that embed governance, observability and semantic capabilities natively.
This fragmentation has created a bottleneck. Despite enterprises spending close to $40 billion on generative AI over the last two years, MIT research found only 5% could point to a real business return.
Major acquisitions echo this shift. Salesforce's purchase of Informatica and IBM's $11 billion acquisition of Confluent reflect enterprise demand for full-stack approaches to data unification. Databricks also recently secured $4 billion in funding as revenue topped a $4.8 billion run-rate.
"As models become more capable, the bottleneck moves to data infrastructure. ClickHouse stood out because it delivers the performance, efficiency and reliability required for AI systems operating at scale."
- Christian Jensen
Partner, Dragoneer Investment Group
ClickHouse at a Glance
ClickHouse targets platform, data engineering and analytics teams at mid-to-large technology enterprises, offering an open-source, column-oriented OLAP database for real-time analytics. Founded in 2021, the company provides a SQL-first OLAP database designed for high-throughput, low-latency analytics on large datasets. As organizations increasingly deploy AI agents, real-time analytics infrastructure becomes essential for monitoring and optimization.
