CITGuru

CITGuru / openduck

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Distributed DuckDB - dual execution and differential storage

435
17
100% credibility
Found Apr 16, 2026 at 401 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Rust
AI Summary

OpenDuck brings cloud-native features like layered storage and split queries to self-hosted DuckDB setups.

How It Works

1
🔍 Discover OpenDuck

You hear about OpenDuck, a free tool that lets everyday DuckDB users tap into cloud data like it's right on their laptop.

2
📥 Get the pieces ready

Download the simple connector and cloud helper so your DuckDB can reach faraway data stores.

3
🚀 Turn on the cloud link

Start the helper with a click to make your remote data ready and waiting.

4
🔗 Link DuckDB to cloud

Tell DuckDB to connect to your cloud data with a quick command, like attaching a new folder.

5
⚡ Mix local and cloud magic

Run queries blending your laptop files with huge cloud tables seamlessly, watching results appear instantly.

🎉 Unlock fast insights

Enjoy speedy analysis on massive datasets without hassle, like having cloud power on your desk.

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Star Growth

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AI-Generated Review

What is openduck?

OpenDuck brings distributed DuckDB to your stack with a self-hosted backend for hybrid execution and differential storage. Attach remote databases via `ATTACH 'openduck:mydb'`, and queries seamlessly split across your local DuckDB instance and remote workers—mixing local CSVs with cloud-scale tables in one SQL statement. Built in C++ for the DuckDB extension and Rust for the gRPC+Arrow protocol, it delivers MotherDuck-style features without the SaaS.

Why is it gaining traction?

It flips DuckDB from single-node embed to distributed query engine, open-sourcing dual execution that pushes subplans to workers while keeping joins local. Developers love the transparent UX—no custom clients, just standard DuckDB—and the open protocol lets you swap backends or scale with Kubernetes. With 369 stars, it's pulling in fans of distributed DuckDB computing as a GitHub distributed systems alternative to proprietary clouds.

Who should use this?

Data engineers running DuckDB workloads that outgrow laptops, like analytics on terabyte Parquet lakes. Teams building distributed DuckDB queries over S3 or Postgres metadata, especially those eyeing DuckDB distributed deepseek integrations or hybrid local/remote joins. Avoid if you need full production HA—it's for prototyping distributed database setups.

Verdict

Grab it for DuckDB distributed execution experiments; the CLI spins up gateway+worker in seconds, and Python bindings make hybrid queries dead simple. At 1.0% credibility and early-stage polish (basic docs, no published extension yet), treat as alpha—build from source, test thoroughly before prod.

(198 words)

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