Coffy - Multi-model Embedded Database Engine for Python
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Coffy - 3 Databases, 1 Pure-Python Library, Zero Setup.
NoSQL • Graph • SQL - all embedded, all local.
Prototype faster. Build without servers.
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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?
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GPT-4o
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?