How ClickHouse Uses PostgreSQL

I am excited to announce that I am joining ClickHouse, Inc. to establish and lead a new research team at ClickHouse Labs.

We ran ClickHouse Managed Postgres and PlanetScale on the same hardware. ClickHouse delivered up to 54% higher throughput with lower latency.

ClickHouse has achieved the AWS Small and Medium Business Competency, joining a select group of AWS Partners recognized for deep expertise in real-time analytics for small and medium businesses.

PostgresBench now includes HA benchmarks, comparing the performance of managed Postgres services under production-style HA configurations. This post explains the architectures behind each service and analyzes the trade-offs between availability guarantees

High-performance full-text search, even on object storage. This deep dive from the ClickHouse engineers explains the new text index design and how it keeps queries fast at scale.

Discover how Postgres managed by ClickHouse compares to its peers in a reproducible, open benchmark.

A Solutions Architect’s experience building a retail analytics platform with AI agents, real-time dashboards, and full observability on the ClickHouse data platform

ClickHouse 26.4 is here! In this release, more features become SQL compatible, COUNT DISTINCT gets faster, EXPLAIN gets even prettier, and more

On June 15, 2016, ClickHouse went open source under the Apache 2.0 license. Ten years later, it's one of the most widely deployed analytical databases in the world.

How we built WAL-RUS, an open-source Rust-based Postgres backup tool that reduces virtual memory usage by over 70% compared to WAL-G while maintaining full compatibility.

chDB embeds a full ClickHouse query engine inside an agent's own process, turning data access, memory, and federation into local function calls instead of network round trips, cutting the latency, retries, and token waste that come with remote queries.

How ClickHouse Managed Postgres reserves, enforces, and sizes huge pages so shared_buffers avoids the per-connection page-table tax that eats RAM and stalls reads on 4KB pages.

The article discusses how PeerDB facilitates large-scale PostgreSQL migrations, specifically achieving a 1TB migration in just 2 hours.

The article discusses the pg_stat_ch extension for PostgreSQL, which facilitates the export of metrics to ClickHouse.

ClickHouse 25.

The article discusses the development of chDB, a Python library that integrates ClickHouse with Pandas DataFrames for high-performance SQL querying.

The article presents a curated list of technology blogs that focus on performance optimizations, algorithms, database development, and more, aimed at helping software engineers find valuable resour...

The article discusses the implementation of a PostgreSQL setting (GUC) for the pg_clickhouse extension, focusing on optimizing the parsing of key/value pairs for session settings.

The article highlights Alexey's favorite features introduced in ClickHouse throughout 2025, including lightweight updates, data lake support, and advancements in text and vector indexing.

This article compares the UPDATE performance of ClickHouse and PostgreSQL, highlighting ClickHouse's significant speed advantages in bulk updates while also acknowledging PostgreSQL's strengths in ...

ClickHouse Release 25.

This article discusses the significant performance improvements achieved in ClickHouse's SQL UPDATE operations, demonstrating how they can be up to 1,000× faster than traditional mutation methods t...

This article discusses the innovative approach ClickHouse has taken to implement fast SQL-style UPDATEs in its column store architecture.

This article discusses how ClickHouse addresses the challenges of row-level updates in column stores by treating updates as inserts.

This article explores a bug encountered by the ClickPipes team related to logical replication slot creation in PostgreSQL read replicas, where a query could not be terminated by standard methods.

The article discusses how Dash0 transitioned to using ClickHouse as a core database technology for their observability platform, leveraging its efficiency and scalability to handle OpenTelemetry da...

The article discusses the implementation of Make Before Break scaling mechanics for ClickHouse Cloud, focusing on the transition from a single StatefulSet architecture to a more flexible MultiSTS a...

This article provides a comprehensive guide on integrating PostgreSQL with ClickHouse using Change Data Capture (CDC) for real-time analytics.

The article discusses the One Billion Documents JSON Challenge, comparing the performance of ClickHouse against other popular databases like MongoDB, Elasticsearch, DuckDB, and PostgreSQL in storin...

This article discusses building single page applications (SPAs) using ClickHouse with a focus on a 'client only' architecture.

ClickHouse Release 24. 4 introduces significant enhancements including recursive common table expressions (CTEs), the QUALIFY clause for window functions, and improved join performance.

ClickHouse Release 23. 11 introduces a wealth of new features, performance optimizations, and bug fixes, enhancing its capabilities for data processing and analytics.

This article explores how to integrate ClickHouse with OpenAI models using User Defined Functions (UDFs) to enhance SQL workloads with AI capabilities.

This article compares ClickHouse and Snowflake for real-time analytics, highlighting their architectural similarities and differences, performance benchmarks, and migration strategies.

The article details the construction of ClickHouse's Internal Data Warehouse (DWH), emphasizing its architecture, data sources, and operational strategies.

This article continues the series on building a Change Data Capture (CDC) pipeline from PostgreSQL to ClickHouse, detailing the configuration and steps necessary to implement a functional pipeline.

This article serves as an introductory guide to implementing Change Data Capture (CDC) between PostgreSQL and ClickHouse, utilizing native features and tools like Debezium and Kafka.

The article discusses five methods for database obfuscation, emphasizing the importance of using realistic data for performance testing in analytical databases like ClickHouse.

This article explores the integration of ClickHouse and PostgreSQL, focusing on how to leverage PostgreSQL data in ClickHouse for enhanced query performance and how to push analytical results back ...

This article provides a comprehensive introduction to the various data formats supported by ClickHouse, focusing on how to effectively import and export data using these formats.

This article explores the integration of PostgreSQL and ClickHouse, highlighting their complementary strengths in handling transactional and analytical workloads.

This article explores the use of window and array functions in ClickHouse to analyze Git commit sequences.

The ClickHouse 22.