chdb-datastore

Name: chdb-datastore
Availability: InStock
Author: makisuo

Replace pandas workflows with a ClickHouse-backed DataStore preserving the pandas API.

1.6k|107|Updated Feb 15, 2026

Search Tags:#pandas #data-analysis #clickhouse #datastore #connectors #cross-source

Ready to run

npx skills add https://github.com/Makisuo/maple --skill chdb-datastore-makisuo

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: chdb-datastore
Source: https://github.com/Makisuo/maple/tree/main/.agents/skills/chdb-datastore
Command: npx skills add https://github.com/Makisuo/maple --skill chdb-datastore-makisuo

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Drop-in pandas replacement that delivers ClickHouse-powered analytics, dramatically speeding up data workflows without changing pandas code.

Core Features & Use Cases

Pandas-compatible API via DataStore backed by ClickHouse for large-scale analytics.
Connects to 16+ data sources and 10+ file formats with seamless cross-source joins.
Use cases include accelerating pandas pipelines, querying remote databases as DataFrames, and joining data across sources.

Quick Start

Install chdb, replace your pandas import with import chdb.datastore as pd, and run a small DataStore example to verify the setup.

Frequently Asked Questions about chdb-datastore

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I speed up slow pandas workflows without changing my code?▼

You can accelerate slow pandas workflows by replacing your pandas import with a ClickHouse-backed DataStore. It preserves the pandas API while executing scalable query operations, delivering faster large-scale analytics without code modifications.

Can I join data across multiple databases and cloud storage using pandas?▼

Yes, cross-source joins across databases and cloud storage are possible using this DataStore. It connects to 16+ data sources and 10+ file formats, allowing you to query and join remote data as DataFrames.

What is a ClickHouse-backed DataStore and how does it work?▼

A ClickHouse-backed DataStore is a data layer that preserves the pandas API while executing queries in ClickHouse. It provides scalable query execution for large datasets, replacing in-memory pandas processing with accelerated analytics.

How do I get started using chdb DataStore for data analysis?▼

To start data analysis, install chdb and replace your pandas import with import chdb.datastore as pd. You can then run a small DataStore example to verify the setup and begin querying your connected data sources.

Does this pandas-compatible DataStore support my specific database and file formats?▼

The DataStore supports 16+ data sources and 10+ file formats for cross-source analytics. It connects to remote databases and cloud storage, enabling multi-source connectivity across various formats.

When should I replace pandas with a ClickHouse-backed data layer?▼

You should replace pandas with a ClickHouse-backed data layer when your data workflows become slow and need scalable query execution. It provides accelerated analytics for large-scale data while maintaining a drop-in pandas API.