ClickHouse Scores $400M Series D, $15B Valuation – Expands into LLM Observability & Native Postgres

The Series D funding round for ClickHouse (€400M) is a significant inflection point for the company, shifting it more firmly into the enterprise-grade, AI infrastructure category. The acquisition of Langfuse underscores the growing importance of observability in large language model (LLM) deployments—a space where output quality, bias, and safety are increasingly under scrutiny.

The launch of a native Postgres service marks a strategic push to unify transactional and analytical workflows, reducing latency and system complexity for developers building AI-powered applications. This product move positions ClickHouse not just as a high-performance analytics engine but as a unified data platform—a trend resonant with recent shifts in database and infrastructure architecture.

Growth metrics are notable: 3,000+ customers and more than 250% year-over-year ARR growth suggest that ClickHouse’s adoption is broadening beyond early AI/ML adopters into mainstream enterprise use. Moreover, inclusion of major companies like Meta, Tesla, and others in its user base both validates its scalability and amplifies competitive pressure on incumbents like Snowflake, Databricks, and open-source project-driven rivals.

Valuation and capitalization dynamics also bear watching. While the precise post-money valuation is not disclosed in all sources, independent reporting suggests a valuation in the neighborhood of $15 billion. If accurate, this represents a steep appreciation from the $6.35 billion post-money valuation following its Series C in mid-2025.

Strategic implications:

• ClickHouse’s trajectory makes it a critical infrastructure provider in the AI era; this could make it a target for strategic acquirers or further large-scale investment, especially given data infrastructure’s central role.
• Its dual strategy—rewriting internal product stack (transactions + analytics) and acquiring specialized observability toolsets—suggests that building end-to-end platforms is becoming necessary to compete.
• The investor syndicate diversity signals continued capital allocation toward companies enabling AI in production; this may fuel competition and valuations in the infrastructure space even further upward.

Open questions and risks:

• Can ClickHouse successfully balance its open-source roots with enterprise demands for transactional consistency, governance, and support? The native Postgres extension raises expectations.
• How well will the integrated observability stack perform, especially in production-scale LLM settings, where performance, reliability, and transparent metrics are essential?
• What competition and regulatory headwinds may arise as ClickHouse expands globally, particularly in regions with stricter data localization, security, and privacy demands?
• How durable is the company’s ARR growth and customer expansion? High growth can expose risks in scalability, cost structure, and operational execution.