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PostgreSQL

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People are sharing how they built a state-of-the-art search engine using PostgreSQL as the core datastore, plus pgvector for embeddings and Qwen3 embeddings for retrieval. The focus is on end-to-end implementation details for vector-based search on Postgres.

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Also known as postgres·postgresql 17·postgresql 18·pgsql·psql

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Key Takeaway A recent build demonstrates SOTA-style search by combining PostgreSQL, pgvector, and Qwen3 embeddings.
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SOTA vector search PostgreSQL + pgvector Qwen3 embeddings postgres postgresql 17
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How we built a SOTA search engine using PostgreSQL, pgvector, and Qwen3 embeddings [P]

People are sharing how they built a state-of-the-art search engine using PostgreSQL as the core datastore, plus pgvector for embeddings and Qwen3 embeddings for retrieval. The focus is on end-to-end implementation details for vector-based search on Postgres.

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  • How we built a SOTA search engine using PostgreSQL, pgvector, and Qwen3 embeddings [P] r/MachineLearning
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What's next?

We are already providing value to our customers by enabling Geo on staging because the Geo team can test and validate Geo at scale at lot easier. Next up is enabling automatic runs of our end-to-end test on staging, which would reduce the manual testing burden even further. There are also some other improvements, such as enabling high-availability configurations of PostgreSQL using Patroni on Geo nodes that we would like to test on staging. Even though enabling Geo on staging is already very useful, it is just a step forward to rolling out Geo on GitLab.com in production. We are currently eval

Why we enabled Geo on the staging environment for GitLab.com
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