Introduction

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║   client   ║░───API──▶║  ┃    Memory/    ┃────▶┃    Object    ┃  ║░
║            ║░         ║  ┃   SSD Cache   ┃     ┃ Storage (S3) ┃  ║░
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║  ┏━━━━━━━━━━━━━━━━━━━━┓  ║░
║  ┃    Memory/SSD      ┃  ║░
║  ┃      Cache         ┃  ║░
║  ┗━━━━━━━━┳━━━━━━━━━━━┛  ║░
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║  ┏━━━━━━━━━━━━━━━━━━━━┓  ║░
║  ┃    Object Storage  ┃  ║░
║  ┃      (S3)          ┃  ║░
║  ┗━━━━━━━━━━━━━━━━━━━━┛  ║░
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turbopuffer is a fast, object-storage native search engine. We service 1T+ documents, 10M+ writes/s, and 25k+ queries/s.

Using only object storage for state and NVMe SSD with memory cache for compute, turbopuffer scales low-latency queries to petabyte scale. This makes turbopuffer as fast as in-memory search engines when cached, but far cheaper to run.

turbopuffer has many features you'd expect from a database optimized for search, including:

• Filters, against an inverted index
• Text search, ranking and boosting
• Vector search, >90% recall, combined with any filters, dense & sparse
• Regex search, with fast trigram regex indexes
• Branching, copy-on-write namespaces
• Encryption, your key or your customer's
• Multi-tenant (default), single-tenant, or BYOC deployments

turbopuffer's tradeoffs for its excellent economics and scalability are higher write latency (p90=248ms for 512KB upserts) from writing directly to object storage, and occasional cold queries for uncached or unpinned data (p90=1214ms on 1M documents). These are excellent tradeoffs for search.

Using object storage as the sole source of truth enables operations like branching — a copy-on-write clone of any namespace, created in constant time regardless of size, with fully independent reads and writes afterward.

To get started with turbopuffer, see the quickstart guide.