turbopuffer
Fast vector and full-text search engine built on object storage — 10x cheaper and infinitely scalable
Free tier available·Technical·API available
Key strengths
10x cheaper than alternativesBuilt on object storage (S3)Extremely scalable (1T+ documents, 10M+ writes/s, 100k+ queries/s)Low latency (sub-10ms p50 for warm namespaces)Vector search and full-text search (BM25) with hybrid searchMetadata filteringAutomatic scaling
Free tier + paid plans · from $16 USD/mo
San Francisco, USA
Founded 2023
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Recent changes
- Free tier: removed
- Starting price: $0/mo → $16/mo
- Plans updated: Three plans: Launch ($16/mo min), Scale ($256/mo min), Enterprise (>=$4,096/mo). Usage-based pricing: Storage ≤$0.33/GB, Writes ≤$2.00/GB, Queries ≤$1.00/PB. Enterprise has 35% usage premium.
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turbopuffer is purpose-built for AI/ML engineers and developers working on search and retrieval workloads at scale. Ideal technical use cases include:
- Retrieval-Augmented Generation (RAG): Index and retrieve high-dimensional embeddings with sub-10ms p50 latency for warm namespaces, enabling fast LLM context retrieval
- Semantic search: Run approximate nearest-neighbor vector queries over 1T+ document corpora backed by S3
- Hybrid search pipelines: Combine BM25 full-text scoring with vector similarity in a single query, with metadata filtering for precise result control
- Recommendation systems: Power large-scale item or content similarity lookups at 100k+ queries/second
- High-throughput ingestion: Ingest at up to 10M+ writes/second without manual scaling intervention
- Cost-sensitive architectures: Replace expensive dedicated vector database clusters with an S3-backed solution at ≤$0.33/GB storage and ≤$1.00/PB query costs
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