Chroma vs turbopuffer
Comparing two vector database platforms on pricing, features, free tier, and trade-offs.
Quick summary
Chroma — The AI-native open source embedding database. Chroma is an open-source embedding database designed for simplicity, with Python-first DX, perfect for prototyping and small-to-medium RAG apps.
turbopuffer — Serverless vector search on object storage. turbopuffer is a serverless vector database built on S3, offering very cheap storage pricing and pay-per-query model — designed for RAG at scale without fixed pod costs.
Feature comparison
| Feature | Chroma | turbopuffer |
|---|---|---|
| Pricing model | Freemium | Paid |
| Starting price | Usage-based | Usage-based |
| Free tier | Yes | No |
| Open source | Yes | No |
| Type | Hybrid | Serverless |
| Free Tier | Self-host unlimited | None |
| Serverless | No | Yes |
| Self-hosted | Yes | No |
| Multi-tenant | No | Yes |
| Hybrid Search | No | Yes |
| Max Dimensions | 16384 | 10000 |
| Metadata Filtering | Yes | Yes |
Chroma
The AI-native open source embedding database
Pros
- Dead simple Python API
- Fast local development
- Fully open source
- Great for prototyping
Cons
- Less mature at production scale
- No hybrid BM25 search
- Managed cloud relatively new
turbopuffer
Serverless vector search on object storage
Pros
- Storage on S3 — extremely cheap
- Pay per query, no pod hours
- Good for cold / infrequently-queried data
- Simple API
Cons
- Higher query latency than Pinecone/Qdrant
- No free tier
- Closed source
Which should you choose?
Choose Chroma if you value open source and want the option to self-host, and a free tier is important for your stage. Choose turbopuffer if you need production-grade features and are ready to pay.