SQLite Vector is now Nix Flake Ready! ❄️

Great news for the Nix community and Edge AI developers: SQLite Vector now has first-class Nix Flake support!

We at Cowork AI are huge fans of the work being done by the SQLite AI team. They have built an incredible tool—unlike other vector stores that require heavy external services or complex indexing phases, SQLite Vector is an ultra-lightweight extension that allows you to store and search embeddings directly in standard SQLite tables with zero pre-indexing. It’s built for the edge, extremely fast, and memory-efficient.

To help make this powerful tool even more accessible, Cowork AI contributed a Pull Request (PR #38) to add full Nix Flake support, and we are thrilled that the SQLite AI team has merged it!

⚡️ What this means for you #

With the newly merged flake.nix, using SQLite Vector in reproducible environments just got significantly easier.

🛠️ Instant Development Environment #

Gone are the days of manually compiling C extensions or fighting with system library mismatches. You can now drop into a fully configured development shell with a single command:

$ nix develop github:sqliteai/sqlite-vector
SQLite Vector extension available at: /nix/store/zsq...-sqlite-vector-0.9.53/lib/vector.dylib
Load it in sqlite3 with: .load /nix/store/zsq...-sqlite-vector-0.9.53/lib/vector.dylib

$ sqlite3
SQLite version 3.51.1 2025-11-28 17:28:25
Enter ".help" for usage hints.
Connected to a transient in-memory database.
Use ".open FILENAME" to reopen on a persistent database.
sqlite> .load /nix/store/zsq...-sqlite-vector-0.9.53/lib/vector.dylib
sqlite> select vector_version();
vector_version()
----------------
0.9.53

This sets up everything you need—SQLite, the compiler toolchain, and the built extension. It even exports a SQLITE_VECTOR_LIB environment variable, so you can test it immediately.

📦 Build Your Own Powered-Up SQLite #

The real power of Flakes comes when you integrate them into your own projects. You can now easily create a custom SQLite package that has the vector extension pre-installed and loaded by default.

For example, you can define a Nix derivation that wraps the standard sqlite and automatically loads sqlite-vector. This ensures that every developer on your team (and your CI/CD pipeline) uses the exact same binary with the exact same vector capabilities.

🧩 Seamless Integration for Apps #

Whether you are building a RAG application in Python, a Go microservice, or a Rust CLI, you can now add sqlite-vector as a standard input to your project’s flake.nix. This allows you to compile and link your application against the extension with guarantees of reproducibility.

🤝 Open Source Collaboration #

We want to extend a huge thank you to the SQLite AI team for building such a robust extension and for being open to community contributions. At Cowork AI, we believe in the power of open source to make AI tools more accessible and reliable for everyone.

Check out the repository and give it a spin: github.com/sqliteai/sqlite-vector

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