Chroma vs pgvector(2026)
Chroma is better for teams that need easiest to get started. pgvector is the stronger choice if no new infrastructure. Chroma is open-source (from $0) and pgvector is open-source (from $0).
Full feature breakdown, pricing details, and pros & cons below.
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Chroma
Chroma is the leading open-source embedding database for LLM applications. With a simple Python/JavaScript API, it is the easiest way to add memory and context to AI apps.
Starting at $0
Visit Chromapgvector
pgvector adds vector similarity search directly to PostgreSQL — store embeddings alongside your relational data and run nearest-neighbor searches with standard SQL.
Starting at $0
Visit pgvectorHow Do Chroma and pgvector Compare on Features?
| Feature | Chroma | pgvector |
|---|---|---|
| Pricing model | open-source | open-source |
| Starting price | $0 | $0 |
| Open source (Apache 2.0) | ✓ | — |
| In-memory or persistent | ✓ | — |
| Python and JS SDKs | ✓ | — |
| Multi-modal embeddings | ✓ | — |
| Filtering | ✓ | — |
| LangChain/LlamaIndex integration | ✓ | — |
| Simple API | ✓ | — |
| PostgreSQL extension | — | ✓ |
| L2/inner product/cosine distance | — | ✓ |
| IVFFLAT indexing | — | ✓ |
| HNSW indexing | — | ✓ |
| Standard SQL | — | ✓ |
| Works with Supabase/RDS | — | ✓ |
| Exact + ANN search | — | ✓ |
Chroma Pros and Cons vs pgvector
Chroma
pgvector
Should You Use Chroma or pgvector?
Choose Chroma if…
- •Easiest to get started
- •Perfect for prototyping
- •Great LLM framework integrations
Choose pgvector if…
- •No new infrastructure
- •Works with existing Postgres
- •SQL interface