pgvector Without Embeddings: When a Feature Vector Beats Semantic Search
This story is from 2026-09-26. It is preserved in the archive; the latest stories are on the live feed.
Almost every pgvector tutorial starts the same way. Take some text, run it through an embedding model, store the resulting vector, and search it with natural language. That is a real and useful pattern, and it is also why most engineers walk away thinking pgvector is a tool for one job: semantic se…
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- 2026-09-26 12:45 · DEV Community — AI
pgvector Without Embeddings: When a Feature Vector Beats Semantic Search