chDB

chDB is a fast in-process SQL OLAP Engine powered by ClickHouse v25.8.2.1. You can use it when you want to get the power of ClickHouse in a programming language without needing to connect to a ClickHouse server.

Key features

• In-process SQL OLAP Engine - Powered by ClickHouse, no need to install ClickHouse server
• Multiple data formats - Input & Output support for Parquet, CSV, JSON, Arrow, ORC and 70+ more formats
• Minimized data copy - From C++ to Python with python memoryview
• Rich Python Ecosystem Integration - Native support for Pandas, Arrow, DB API 2.0, seamlessly fits into existing data science workflows
• Zero dependencies - No need for external database installations
• DataStore API - Pandas-compatible API with SQL optimization, supporting 630+ methods

DataStore: Pandas-Compatible API

NEW! DataStore provides a pandas-compatible API that combines familiar pandas syntax with ClickHouse performance.

One-Line Migration

# Just change your import - your pandas code works unchanged
- import pandas as pd
+ from chdb import datastore as pd

df = pd.read_csv("data.csv")
result = df[df['age'] > 25].groupby('city')['salary'].mean()

Performance Highlights

Operation	pandas	DataStore	Speedup
GroupBy count	347ms	17ms	19.93x
Complex pipeline	2,047ms	380ms	5.39x
Filter+Sort+Head	1,537ms	350ms	4.40x

Benchmarks on 10M rows

DataStore Features

• 630+ API methods - 209 pandas DataFrame methods, 185+ accessor methods
• Lazy evaluation - Operations compile to optimized SQL
• SQL pushdown - Filters and aggregations run at the data source
• Universal data sources - Read from files, S3, databases, data lakes

Learn more: DataStore Documentation

What languages are supported by chDB?

chDB has the following language bindings:

• Python - API Reference
• Go
• Rust
• NodeJS
• Bun
• C and C++

How do I get started?

• If you're using Go, Rust, NodeJS, Bun or C and C++, take a look at the corresponding language pages.
• If you're using Python, see the getting started developer guide or the chDB on-demand course.

For pandas Users

Start with the DataStore API for a familiar pandas experience with ClickHouse performance:

• DataStore Quickstart - Installation and one-line migration
• Migration from pandas - Step-by-step migration guide
• Pandas Cookbook - Common patterns
• Key Differences - Important differences from pandas
• Performance Guide - Optimization tips

DataStore API Reference

• Factory Methods - Create from files, databases, cloud storage
• Query Building - SQL-style operations
• Pandas Compatibility - 209 compatible methods
• Accessors - .str, .dt, .arr, .json, .url, .ip, .geo
• Configuration - Engine, logging, profiling
• Debugging - explain(), profiling, logging

SQL API Guides

• Python API Reference - Complete SQL API documentation
• JupySQL
• Querying Pandas
• Querying Apache Arrow
• Querying data in S3
• Querying Parquet files
• Querying remote ClickHouse
• Using clickhouse-local database

An introductory video

Watch a brief introduction to chDB and learn how it brings ClickHouse's power to your Python environment:

Performance benchmarks

chDB delivers exceptional performance across different scenarios:

• ClickBench of embedded engines - SQL API performance comparison
• DataFrame Benchmark - DataFrame engines comparison
• DataStore vs Pandas - Up to 20x faster than pandas on common operations

About chDB

• Read the full story about the birth of the chDB project on blog
• Read about chDB and its use cases on the Blog
• Take the chDB on-demand course
• Discover chDB in your browser using codapi examples
• More examples see (https://github.com/chdb-io/chdb/tree/main/examples)

License

chDB is available under the Apache License, Version 2.0. See LICENSE for more information.