ClickHouse Showcases High-Volume PostgreSQL Observability Integration

According to a recent LinkedIn post from ClickHouse, the company is highlighting a PostgreSQL extension called pg_stat_ch that streams detailed query execution events into its analytics engine. The post contrasts this with pg_stat_statements, suggesting the new approach offers more granular timing, percentile, and client-context visibility for database workloads.

The LinkedIn post describes pg_stat_ch as capturing 45 fields per query, including timing, buffer I/O, WAL statistics, CPU, JIT metrics, and client context, and sending them via the native ClickHouse protocol with LZ4 compression. It also notes design choices such as fixed-size events, a shared-memory ring buffer, and dropping events on overflow to avoid impacting PostgreSQL performance.

According to the performance figures cited in the post, testing reportedly achieved 7.7 million events in 30 seconds with no drops and around 11% TPS overhead, while data was compressed from roughly 35GB to 426MB. If these characteristics hold in production, they could strengthen ClickHouse’s positioning in the high-performance observability and analytics segment, potentially making its platform more attractive for enterprises running PostgreSQL at scale.

For investors, the focus on low-overhead, high-resolution telemetry suggests an effort to deepen integration with existing database ecosystems rather than displace them. This could expand ClickHouse’s addressable market by turning PostgreSQL environments into feeders for its analytics platform, supporting usage-based growth and reinforcing its role in performance monitoring and real-time analytical workloads.