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Built on PostgreSQL, Tiger Cloud combines robustness and flexibility to tame your most demanding workloads, from real-time analytics and IoT data to events and vector embeddings.
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Apr 20, 2026
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.
Jun 11, 2024
Introducing pgvectorscale, an open-source PostgreSQL extension that supercharges pgvector’s vector search performance for large-scale vector workloads.
Jun 11, 2024
Meet pgai and pgvectorscale, two new open-source extensions that make PostgreSQL even better for AI applications.
Jun 11, 2024
Read how we equipped PostgreSQL with advanced indexing techniques, making it as fast as other specialized vector databases, like Pinecone.
Jun 11, 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.
May 31, 2024
Hybrid search enables better results by combining keyword and semantic search. Learn how to implement it on PostgreSQL with pgvector and Cohere.
Jul 12, 2023
“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.
Jun 30, 2023
A primer on the pgvector’s Inverted File Flat (ivfflat) algorithm for approximate nearest neighbor search.
