The use case: how Linear deploys turbopuffer
Linear uses turbopuffer as a unified vector and full-text search backend, replacing Elasticsearch and pgvector. It powers hybrid search across issues, documents and projects, similar-issue detection, suggestions during issue creation, and delta sync for returning clients.
More reported results
Figures published in turbopuffer’s case study. They are not independently measured by usedby.
~150ms lower embedding latency
~8s faster for large delta syncs
~4s faster for medium delta syncs (40k–50k actions)
200M+ documents, 30B+ tokens embedded
In the customer’s words
Their responsiveness and shipping velocity make us feel like we are their only customer.It's been fun to work with @turbopuffer on [the new search]. Admittedly keyword based search never really worked great for issues, and the results from embedding+FTS are now actually useful.Other AI tools used by Linear
Other public relationships recorded on usedby.
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turbopuffer users in DevTools & Infrastructure
Companies in the same sector, with public evidence.
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Go straight to the source
Based on turbopuffer’s published case study. We check the public evidence; the results are reported by the vendor.
turbopuffer.com- Last checked
- Nov 12, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The figure: 70%Checked
Printed word for word on the page, near the name of Linear.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of Linear.
- Linear uses turbopufferChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
Linear migrated search off Elasticsearch and pgvector onto turbopuffer and experienced: