RIP, vector database

In one line

turbopuffer is pushing the frontier of search. To do that, we have to fundamentally redesign our storage architecture so the vector index is no longer primary.

Opening excerpt

tpuf v3 is coming: follow along turbopuffer v3 is coming: follow our progress RIP, vector database September 30, 2026 • Dan Harrison (Engineer) We are changing turbopuffer’s storage architecture to take search to the next level. turbopuffer v3 changes how documents and indexes are laid out, written, compacted, and queried in turbopuffer. It will allow us to make search faster in every respect — including text, regex, and vector search — but it also lays the foundation to move many more SQL queries to turbopuffer and make them fast.

turbopuffer launched as a serverless vector database (v1) , highly specialized to the task of serving extremely cheap and reasonably fast vector searches. Object storage as the source of truth gave the economics, and tiered NVMe SSD/memory caches gave the performance. The value of these particular tradeoffs was validated by our earliest customers, including Cursor and Notion.

turbopuffer evolved to have very strong text and regex search (v2), and is being used for many non-search use cases, like Linear’s syncing engine .

(Excerpted from the original; full article via the source link below.)

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