turbopuffer introduced a search feature that allows users to search for 450 million+ code blocks, prompts, and agent session transcripts across repositories.
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Entire searches 450M+ code blocks, prompts, and agent session transcripts on turbopuffer → namespace per repository → hybrid vector + full-text search → 60ms p95 query l…
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turbopuffer
{vector, full-text} search on object storage. fast, cheap, trillion scale. powers Anthropic, Harvey, Notion, and more.
- Industry
- Technology, Information and Internet
- Company size
- 11–50 employees
About turbopuffer
turbopuffer is a fast search engine that combines vector and full-text search using object storage, making all your data easily searchable. Using only object storage for state and NVMe SSD with memory cache for compute, turbopuffer scales horizontally to handle billions of documents. The system caches only actively searched data while keeping the rest in low-cost object storage, offering competitive pricing. Cold queries process 1 million vectors in 500ms (p90), while warm queries take just 20ms (p50). This architecture means it's as fast as in-memory search engines when cached, but far cheaper to run. Storing data in cache and object storage costs less than traditional replicated disk systems, even for frequently accessed data.
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Partnerships
turbopuffer partnered with Applied Compute to post-train a small model for large-scale code search over precomputed indexes at 300 repos.
Products & Services
turbopuffer makes it possible to search every video, image, and 3D model you generate on fal
Products & Services
turbopuffer achieves 300M+ assets
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