When to Use SQLite-Backed Embeddings vs Dedicated Vector DBs

SQLite-backed embeddings are turning heads. The Show HN project vectorlitedb stacks embedding vectors inside a SQLite database, promising a portable setup you can pip install in about 30 seconds ^[1].

What this approach gets right

It gives you a self-contained vector store that runs with your app and avoids a separate service. The vectorlitedb approach emphasizes embedding vectors stored in a .db for portability, with a quick pip install ^[1].

Trade-offs to consider

• Portability and simplicity – Embedding vectors in a SQLite database keeps dependencies small and deployment tidy ^[1].

• Indexing and scaling – As data grows, indexing and scaling can be a challenge versus dedicated vector databases ^[1].

Bottom line

For quick tests and portable apps, SQLite-backed embeddings offer a low-friction start; you’ll want to revisit the architecture if/when needs scale ^[1].

Referenced post shows the appeal of embedding vectors directly in a database and the promise of a lightweight, install-easy workflow with a small footprint ^[1].

References