Receive the latest technical articles and release notes in your inbox.
Most search stacks run four systems to answer one question. You don't need any of them. Build production hybrid search in Postgres with pg_textsearch for BM25, pgvectorscale for vector similarity, and Reciprocal Rank Fusion to combine them. One query. One database.
By Erin Mikail Staples
April 20th, 2026
Introducing pgvectorscale, an open-source PostgreSQL extension that supercharges pgvector’s vector search performance for large-scale vector workloads.
By Avthar Sewrathan
June 11th, 2024
Meet pgai and pgvectorscale, two new open-source extensions that make PostgreSQL even better for AI applications.
By Avthar Sewrathan
June 11th, 2024
Read how we equipped PostgreSQL with advanced indexing techniques, making it as fast as other specialized vector databases, like Pinecone.
By Matvey Arye
June 11th, 2024
Comparing the query latency, query throughput, and cost of Pinecone vs. self-hosted PostgreSQL with pgvector and pgvectorscale on a 50 million vector benchmark.
By Avthar Sewrathan
June 11th, 2024
Hybrid search enables better results by combining keyword and semantic search. Learn how to implement it on PostgreSQL with pgvector and Cohere.
By Haziqa Sajid
May 31st, 2024
“Hello World” for pgvector and LangChain! Learn how to build LLM applications with LangChain framework, using PostgreSQL and pgvector as a vector database for embeddings data.
By Avthar Sewrathan
July 12th, 2023
A primer on the pgvector’s Inverted File Flat (ivfflat) algorithm for approximate nearest neighbor search.
By Matvey Arye
June 30th, 2023
Vector databases add organizational intelligence to AI. Learn how to use PostgreSQL as a vector database for retrieval-augmented generation with pgvector.
By Avthar Sewrathan
June 21st, 2023
