pgvector vs Chroma(2026)
pgvector is better for teams that need no new infrastructure. Chroma is the stronger choice if easiest to get started. pgvector is open-source (from $0) and Chroma is open-source (from $0).
Full feature breakdown, pricing details, and pros & cons below.
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pgvector
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 pgvectorChroma
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 ChromaHow Do pgvector and Chroma Compare on Features?
| Feature | pgvector | Chroma |
|---|---|---|
| Pricing model | open-source | open-source |
| Starting price | $0 | $0 |
| PostgreSQL extension | ✓ | — |
| L2/inner product/cosine distance | ✓ | — |
| IVFFLAT indexing | ✓ | — |
| HNSW indexing | ✓ | — |
| Standard SQL | ✓ | — |
| Works with Supabase/RDS | ✓ | — |
| Exact + ANN search | ✓ | — |
| Open source (Apache 2.0) | — | ✓ |
| In-memory or persistent | — | ✓ |
| Python and JS SDKs | — | ✓ |
| Multi-modal embeddings | — | ✓ |
| Filtering | — | ✓ |
| LangChain/LlamaIndex integration | — | ✓ |
| Simple API | — | ✓ |
pgvector Pros and Cons vs Chroma
pgvector
Chroma
Should You Use pgvector or Chroma?
Choose pgvector if…
- •No new infrastructure
- •Works with existing Postgres
- •SQL interface
Choose Chroma if…
- •Easiest to get started
- •Perfect for prototyping
- •Great LLM framework integrations