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A DuckDB extension to evaluate the Rhai scripting language as part of SQL.
A no code tool to help build pivot tables from any database with a few clicks.
DuckDB extension to fetch pages from Wayback Machine & Common Crawl
Query Elasticsearch data directly from DuckDB
Play the New York Times Connections puzzle with DuckDB!
A DuckDB extension for working with Kaggle datasets
Declarative data quality engine. Define checks in YAML, run anywhere.
A Slackbot built on DuckDB & Claude Code that answers data questions from Slack
🦆 A pre-built AWS Lambda Layer containing DuckDB for Python
DuckDB, DuckLake & Parquet EF Core Provider for analytics at cloud scale — for .NET 10 and EF Core 10 (and Dotnet 11 in Preview)
Utilities for using DuckDB in react
Your data, explored locally — and your AI agents kept on a leash. A federated data explorer with governed agentic access.
A detective for your data. Zero-config data quality monitoring — works with dbt, Postgres, BigQuery, Snowflake. No YAML.
PHP PDO Driver for DuckDB
Run DuckDB inside Excel VBA: pandas-style analytics via in-process SQL + native C bridge. High-speed Range/Array ingestion, Parquet/CSV/JSON I/O.
Privacy-first local data analytics powered by DuckDB.
Cold storage that queries like hot storage. High-ratio JSONL compressor with block-level random access. Query cold storage in seconds — no restore, no full decompression. 5–13% ratio on JSONL logs, 25–57% smaller than gzip. 1-hour window via DuckDB in under 6s. Free for personal and open-source use.
A Snap package for DuckDB
A template for developing DuckDB extensions in Zig
Generate test data. Including null probability definition and various transformations. Output to CSV, Json, Parquet or Excel. Supports nested structures. Powered by duckdb
Open, audit-grade agentic data quality framework with portable industry packs
Lightweight DuckDB query-building client for C#
Data ingestion engine — Singer taps to Parquet in cloud buckets
Virtual warehouse — SQL + Jupyter + AI over cloud Parquet via DuckDB
DuckDB extension to read PFC-JSONL compressed log files with block-level timestamp filtering
YAML-based data pipeline framework that runs both locally and fully in-browser designed for data engineers, ML teams, and SaaS developers who need flexible, SQL-powered pipelines.