---
title: "Introducing chdb Postgres extension: High-performance imports from cloud storage"
description: "The new chdb Postgres extension uses the chDB library, an in-process ClickHouse engine, to import and export data between Postgres and files on cloud storage. In benchmarks using the one-million-row NYC Taxi dataset, chdb ran on four-vCPU, 32-GB ClickHouse Managed Postgres instances and showed the most consistent performance; pg_duckdb and pg_lake took about two to three times longer for CSV, JSON, and Parquet, while aws_s3 supported fewer formats. Its chdb_query() function executes chDB queries, while chdb_hook integrates with COPY for AWS S3, Google Cloud Storage, Azure Blob Storage, local files, and HTTP URLs, with wildcard expansion for multiple files. The extension launches a separate helper application on demand and exchanges ClickHouse Native results through file descriptors, limiting resource use and isolating the PostgreSQL cluster."
---

# Introducing chdb Postgres extension: High-performance imports from cloud storage

[Clickhouse](https://yomu.fyi/company/clickhouse) · Sep 8, 2026

**Type:** Announcement

## Summary

The new chdb Postgres extension uses the chDB library, an in-process ClickHouse engine, to import and export data between Postgres and files on cloud storage. In benchmarks using the one-million-row NYC Taxi dataset, chdb ran on four-vCPU, 32-GB ClickHouse Managed Postgres instances and showed the most consistent performance; pg\_duckdb and pg\_lake took about two to three times longer for CSV, JSON, and Parquet, while aws\_s3 supported fewer formats. Its chdb\_query() function executes chDB queries, while chdb\_hook integrates with COPY for AWS S3, Google Cloud Storage, Azure Blob Storage, local files, and HTTP URLs, with wildcard expansion for multiple files. The extension launches a separate helper application on demand and exchanges ClickHouse Native results through file descriptors, limiting resource use and isolating the PostgreSQL cluster.

## Context

Postgres users need efficient, flexible ways to import and export data in many formats from cloud storage. The source compares chdb with aws\_s3, pg\_duckdb, and pg\_lake, noting differences in performance, supported formats, and resource management.

## Approach / What changed

chdb provides chdb\_query() for executing chDB queries, while chdb\_hook connects COPY to AWS S3, Google Cloud Storage, Azure Blob Storage, local files, HTTP URLs, and wildcard-based file sets. A separate helper application embeds chDB and communicates with the PostgreSQL backend through file descriptors and ClickHouse Native results.

## Takeaways

- chdb supports formats including TSV, CSV, JSON, BSON, Prometheus, Protobuf, Avro, Parquet, Arrow, XML, CapnProto, Markdown, MsgPack, and ORC, along with gzip, zstd, lz4, bz2, snappy, and brotli compression.
- In the NYC Taxi benchmark, pg\_duckdb and pg\_lake took about two to three times longer than chdb for CSV, JSON, and Parquet imports; aws\_s3 approached chdb's performance but supported fewer formats.
- The helper application starts on demand, communicates through STDIN, STDOUT, STDERR, and a configuration file descriptor, then exits after passing results to the PostgreSQL backend.

**Tags:** [chdb](https://yomu.fyi/topic/chdb), [ClickHouse](https://yomu.fyi/topic/clickhouse), [Postgres](https://yomu.fyi/topic/postgres)

- Source: [Clickhouse](https://clickhouse.com/blog/introducing-chdb-postgres)
- Source URL: https://clickhouse.com/blog/introducing-chdb-postgres
- Ingested by Yomu: 2026-09-08T16:00:51.427Z

[Read original post](https://clickhouse.com/blog/introducing-chdb-postgres)