Coffy - 3 Databases, 1 Pure-Python Library, Zero Setup. NoSQL • Graph • SQL - all embedded, all local. Prototype faster. Build without servers.

Tired of setup friction? So was I. I kept running into the same overhead: - Spinning up Neo4j for tiny graph experiments - Switching between SQL, NoSQL, and graph libraries - Fighting frameworks just to test an idea So I built Coffy - a pure-Python embedded database engine that ships with three engines in one library: - coffy.nosql: JSON document store with chainable queries, auto-indexing, and local persistence - coffy.graph: build and traverse graphs, match patterns, run declarative traversals - coffy.sql: SQLite ORM with models, migrations, and tabular exports All engines run in persistent or in-memory mode. No servers, no drivers, no environment juggling. What Coffy is for: - Rapid prototyping without infrastructure - Embedded apps, tools, and scripts - Experiments that need multiple data models side-by-side What Coffy isn’t for: - Distributed workloads or billion-user backends - Coffy is open source, lean, and developer-first. Cureious? coffydb.org

This is truely awesome! Having SQL, NoSQL, *and* graph databases all in one pure-Python library is such a smart move. No more context switching between different tools and frameworks for little experiments — ngl, that's a huge time saver. Kinda genius imo. How's the performance compared to using dedicated databases for larger datasets, though?

Coffy

Multi-model Embedded Database Engine for Python

Multi-model Embedded Database Engine for Python