turbopuffer is a serverless search engine that combines vector and full-text (BM25) search built from first principles directly on object storage. It exposes a single REST API organized around namespaces — each namespace stores documents with vector embeddings, attributes, and full-text indexes — and supports approximate nearest neighbor, full-text BM25, and hybrid query patterns with attribute filtering, ranking, and aggregation. The platform is used in production by Anthropic, Cursor, Notion, Linear, Superhuman, Pylon, Readwise, and Telus, and handles 4T+ documents, 10M+ writes/s, and 25k+ queries/s across customer fleets. Official client libraries ship for Python, TypeScript, Go, Java, Ruby, and C#, generated from a public OpenAPI 3.1 specification via Stainless. Pricing is tiered (Launch, Scale, Enterprise) with usage-based metering on storage, writes, and queries on top of monthly minimums.
turbopuffer publishes 1 API on the APIs.io network: Namespaces API. Tagged areas include Vector Search, Full-Text Search, Hybrid Search, BM25, and Serverless.
turbopuffer’s developer surface includes authentication, documentation, GitHub presence, pricing, engineering blog, and 15 more developer resources.
Open Source Surface applies to this provider. This product is open source and we
read its repository directly, so Open Source Surface carries
10 points of the composite. It is scored from what the repository actually
publishes — a security policy, a contribution guide, a release history, a code of conduct — read live from the
provider rather than inferred from our own catalog pointers.
This facet adds; nothing was taken away to make room for it. An open-source project is not excused from
the commercial facets, because exemption would strip it of the points it does earn.
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Create-or-Update Ergonomics applies to this provider. This API accepts writes, so it
carries 10 points of the composite. It is scored from the published contracts
themselves: whether a caller can create-or-update in one call, whether the write accepts a key the caller already
holds, and whether the response says which branch ran. Without that, every write needs a search-and-branch in
front of it, and the first time that check is skipped a duplicate record is created.
Scored against the observed mean rather than raw — a provider at the catalog average is unchanged by this facet,
not penalised by it.
The six quality facets above are damped to 80 points between them,
because the conditional facet above carries the other
20. That is why each facet's contribution is shown against a damped
maximum: raising a quality facet moves the composite by 80% of its nominal
weight, not 100%. The full arithmetic is at apis.io/rating/.
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Endpoints for upserting, patching, and deleting documents within a namespace. Writes are batched into a per-namespace write-ahead log and become queryable once committed to obje...
Unified query endpoint that runs vector ANN, full-text BM25, and hybrid queries against a namespace, with attribute filters, top-k, aggregation groups, and ranking controls. Sup...
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