Chdb Datastore

This teaches Claude to work with chdb's DataStore, which is essentially pandas with a ClickHouse engine underneath. The main pitch is you can swap `import pandas as pd` for `import chdb.datastore as pd` and your existing code gets faster through lazy execution and SQL compilation. Where it really shines is cross-source joins: pull a table from MySQL, join it with a parquet file, aggregate, done. Supports 16+ connectors including S3, PostgreSQL, MongoDB, Delta Lake. The skill covers the full pandas-compatible API (209 methods), connection patterns for different sources, and when to use this versus raw SQL queries. If you're hitting pandas performance walls or need to join data across databases and files without ETL, this is the move.

skills.sh installs: 8.1K
GitHub stars: 565
last updated: Aug 21, 2026

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Install

$ npx -y skills add clickhouse/agent-skills --skill chdb-datastore --agent claude-code

Installs into .claude/skills of the current project.

Files

chdb DataStore — It's Just Faster Pandas

The Key Insight

# Change this:
import pandas as pd
# To this:
import chdb.datastore as pd
# Everything else stays the same.

DataStore is a lazy, ClickHouse-backed pandas replacement. Your existing pandas code works unchanged — but operations compile to optimized SQL and execute only when results are needed (e.g., print(), len(), iteration).

pip install chdb

Decision Tree: Pick the Right Approach

1. "I have a file/database and want to analyze it with pandas"
   → DataStore.from_file() / from_mysql() / from_s3() etc.
   → See references/connectors.md

2. "I need to join data from different sources"
   → Create DataStores from each source, use .join()
   → See examples/examples.md #3-5

3. "My pandas code is too slow"
   → import chdb.datastore as pd — change one line, keep the rest

4. "I need raw SQL queries"
   → Use the chdb-sql skill instead

Connect to Any Data Source — One Pattern

from datastore import DataStore

# Local file (auto-detects .parquet, .csv, .json, .arrow, .orc, .avro, .tsv, .xml)
ds = DataStore.from_file("sales.parquet")

SKILL.md on GitHub