turbopuffer vs Weaviate
Comparing two vector database platforms on pricing, features, free tier, and trade-offs.
Quick summary
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.
Weaviate — Open source vector database with built-in ML. Weaviate is an open-source vector database with native multi-modal search, built-in vectorizer modules, hybrid search, and cloud or self-hosted deployment.
Feature comparison
| Feature | turbopuffer | Weaviate |
|---|---|---|
| Pricing model | Paid | Freemium |
| Starting price | Usage-based | $25/mo |
| Free tier | No | Yes |
| Open source | No | Yes |
| Type | Serverless | Hybrid |
| Free Tier | None | 14-day sandbox |
| Serverless | Yes | Yes |
| Self-hosted | No | Yes |
| Multi-tenant | Yes | Yes |
| Hybrid Search | Yes | Yes |
| Max Dimensions | 10000 | 65535 |
| Metadata Filtering | Yes | Yes |
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
Weaviate
Open source vector database with built-in ML
Pros
- Fully open source, self-hostable
- Built-in vectorizer modules
- Native multi-modal (text + image)
- GraphQL API
Cons
- Heavier ops than Pinecone if self-hosting
- Cloud tier pricing more complex
- Community smaller than Pinecone's
Which should you choose?
Choose turbopuffer if you need production-grade features and are ready to pay. Choose Weaviate if you value open source and want the option to self-host, and a free tier is important for your stage.