Hi I'm Ruddy
Source: Dev.to
Most DuckDB tooling falls into one of three buckets: a browser‑based WASM tool with all the overhead that implies, a thin SQL console bolted onto the engine, or a Python notebook that happens to use DuckDB on the side. I wanted something different — a proper Mac app that runs the native DuckDB binary, feels at home on macOS, and handles the full data workflow without switching tools. That’s Ruddy.
What it does
Native DuckDB engine
No WASM. No middleware. The real binary runs locally, which matters for performance on larger files and for features that WASM builds don’t fully expose.
Notebooks powered by Marimo
Python + SQL notebooks with installable native libraries. Not a dumbed‑down cell runner — you can build full analyses and share them.
AI agent — Ruddynie
An agent that runs queries, builds notebooks, and connects to MCP servers. Bring your own model: Claude, Gemini, OpenAI, or OpenRouter.
Visual query builder
Built on top of the ERD view — you can click together joins without writing SQL. Useful for exploration and for less SQL‑fluent teammates.
Spatial support
Geospatial data renders as maps out of the box, powered by DuckDB’s spatial extension.
Git integration
Version control built into the editor. SQL and notebook files are first‑class citizens in your repo.
Catalog + ERD
Clean schema browser with auto‑generated entity‑relationship diagrams.
What it connects to
Local files (Parquet, CSV, JSON), cloud data sources, and remote HTTP endpoints. DuckDB’s httpfs and S3 support is exposed natively.
Pricing
Early‑access pricing while we’re still in this phase, with a 7‑day free trial:
- $1.25 / month — all features, auto‑renewal
- $7.50 — 6 months upfront
- $15 one‑time — pay once, use forever
Why macOS‑native
DuckDB is fast. Running it inside a browser sandbox or an Electron shell adds latency and limits what you can do with native libraries, memory management, and OS integration. A native Mac app lets the engine breathe.
Download and try it: ruddy.pro
Happy to answer questions about the stack, the product, or how the AI agent is architected.