select open change scope Open full search

PG.CENTER connects PostgreSQL documentation, reference, and ecosystem knowledge. Maintained by Pigsty.

Extensions / AI and vectors

pg_semantic_cache

Caches query results and retrieves semantically similar results using pgvector embeddings and configurable eviction policies.

pgext.cloud · Source code · Documentation · License text · Control file

Overview

Packagepg_semantic_cache
Version0.1.0-beta4
PostgreSQL versions14 · 15 · 16 · 17 · 18
RepositoryUnspecified
Extension typeStandard
Project statusPreview
Requires CREATE EXTENSIONYes
Requires preloadNo
TrustedNo
RelocatableNo
Schemasemantic_cache
Stars8
Latest commit2026-08-24
Latest release2026-02-24
Catalogue updated2026-08-30

Related extensions

Requires

plpgsqlPL/pgSQL procedural language
vectorvector data type and ivfflat and hnsw access methods

See also

vectorvector data type and ivfflat and hnsw access methods
vectorizeThe simplest way to do vector search on Postgres
pgmnemoSingle-plan multimodal agent memory for PostgreSQL
pgedge_vectorizerAsynchronous text chunking and embedding generation for PostgreSQL using background workers and pgvector.
pgturbohybridhybrid vector and BM25 search for PostgreSQL on top of pgvector
rds_aiAlibaba Cloud RDS extension for calling LLMs, generating embeddings, semantic retrieval, and end-to-end RAG from SQL
llama_embedllama.cpp embedding extension for dense and multivector search
pg_colbert_llamaColBERT embedding companion extension for pgturbohybrid
pgturbohybrid_experimentalexperimental sparse and multivector features for pgturbohybrid
pg_cuvs⚡ Blazing-fast GPU vector search for PostgreSQL powered by NVIDIA cuVS.
pgcontextVector, filter-aware HNSW, and hybrid retrieval over authoritative PostgreSQL tables.