Turbopuffer
Serverless vector database with fast search and namespace isolation.
About
Turbopuffer is a managed search engine that runs vector similarity search and BM25 full-text search directly from object storage, an architecture that sets it apart from memory-resident vector databases. Data lives in S3 with a memory and SSD cache layer in front, which keeps costs low for large corpora while still serving warm queries at p50 latencies under 10 milliseconds. Each workload is isolated in its own namespace, and the service scales to billions of vectors with metadata filtering and hybrid queries that combine semantic and keyword relevance. Pricing is usage based rather than instance based, so idle namespaces cost little. It is a closed source commercial service accessed through an HTTP API with official Python and JavaScript clients. Companies including Cursor, Notion, and Linear use it as retrieval infrastructure for AI features, and it suits teams that want production RAG search without operating their own vector database cluster.
Should you use Turbopuffer?
Pick it when
Pick Turbopuffer when you need production vector and BM25 search over large corpora or many per-tenant namespaces, want usage-based pricing where idle data costs little, and would rather call an API than run a vector database cluster.
Look elsewhere when
Skip it if you need self-hosting, source access, or data that never leaves your own infrastructure: it is closed source and API-only. Qdrant, Milvus, or LanceDB give you open code, and pgvector keeps vectors beside Postgres data.
Alternatives to Turbopuffer
- Pinecone
Also closed and fully managed, but bundles hosted embedding and reranking models plus MCP servers; pick it when you want those in one service, not search alone.
- Qdrant
Open source and self-hostable with a managed option, so you can leave the vendor; you size and run the cluster yourself unless you pay for hosting.
- LanceDB
Open source and embedded, scaling from laptop to production with a managed cloud option; no per-query bill, but you operate storage yourself.
- Vespa
Self-hosted or Vespa Cloud with hybrid text and vector search plus ML ranking at billion scale; open source, but much harder to operate.
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Details
- Category
- Vector Databases & Embeddings
- Price
- Freemium
- Platform
- API
- Difficulty
- Beginner (1/5)
- Added
- Apr 3, 2026