LanceDB vs sqlite-vec
A side-by-side comparison of LanceDB and sqlite-vec, two Vector DB tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
| Attribute | LanceDB | sqlite-vec |
|---|---|---|
| Category | Vector DB | Vector DB |
| Pricing (differs) | FREEMIUM | FREE |
| License (differs) | Open core | Open source |
| Deployment (differs) | Hybrid | Local |
| Platforms (differs) | API, Linux, macOS, Windows | API |
| Model support | Model-agnostic | Model-agnostic |
| Vendor (differs) | LanceDB | Alex Garcia |
The honest brief
LanceDB
Runs in-process on the disk-efficient Lance format — no server, no port, zero-copy reads; strong on multimodal data.
- Embeds in your app; runs on edge/desktop
- Disk-efficient Lance format, low cost
- Native multimodal (text, image, video)
- Hybrid vector + full-text + SQL queries
- Newer; smaller community than Qdrant/Milvus
- Managed cloud tier still maturing
- Multi-process concurrent access limits
- Fewer framework integrations, less tooling
sqlite-vec
Embeds vector search inside the SQLite file itself, so RAG can run fully local — in the browser via WASM or on a Raspberry Pi — with no server.
- Zero dependencies, pure C
- Runs anywhere SQLite runs
- Bindings for Python, JS, Ruby, Go, Rust
- Local-first, no server needed
- MIT / Apache 2.0 licensed
- Exhaustive (brute-force) search, not ANN
- Not built for very large datasets
- Single-node, embedded only