Chroma vs sqlite-vec
A side-by-side comparison of Chroma and sqlite-vec, two Vector DB tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
| Attribute | Chroma | sqlite-vec |
|---|---|---|
| Category | Vector DB | Vector DB |
| Pricing (differs) | FREEMIUM | FREE |
| License (differs) | Open core | Open source |
| Deployment (differs) | Hybrid | Local |
| Platforms | API | API |
| Model support | Model-agnostic | Model-agnostic |
| Vendor (differs) | Chroma | Alex Garcia |
| Capabilities (differs) |
|
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The honest brief
Chroma
Runs embedded inside your Python process — the lowest-friction way to prototype RAG before you need a server at all.
- Pip-install, embedded in-process
- Minimal setup for prototyping
- Open-source
- Hosted option when you outgrow local
- Not built for massive scale
- Fewer enterprise features than rivals
- Python-centric ergonomics
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
When to pick which
Both cover Vector search.
Pick Chroma if you need Embeddings.
- Embeddings (secondary capability)
They also differ on:
- Pricing
- FREEMIUM · FREE
- License
- Open core · Open source
- Deployment
- Hybrid · Local