— a simple, embedded vector database that stores everything in a single file, just like SQLite.

The problem:

If you’re a developer building AI apps, you usually have two choices for vector search

- Set up a server (e.g. Chroma, Weaviate) - Use a cloud service (e.g. Pinecone)

That works for production, but it’s overkill when you just want to:

- Quickly prototype with embeddings - Run offline without cloud dependencies - Keep your data portable in a single file

The inspiration was *SQLite* during development — simple, local, and reliable.

The solution:

So I built VectorLiteDB

- Single-file, embedded, no server - Stores vectors + metadata, persists to disk - Supports cosine / L2 / dot similarity - Works offline, ~100ms for 10K vectors - Perfect for local RAG, prototyping or personal AI memory

Feedback on both the tool and the approach would be really helpful.

- Is this something that would be useful - Use cases you’d try this for