⚡ Blazing-fast GPU vector search for PostgreSQL powered by NVIDIA cuVS.
pgext.cloud · Source code · Documentation · Control file
| Package | pg_cuvs |
|---|---|
| Version | 0.5.0 |
| Repository | Unspecified |
| Extension type | Standard |
| Project status | Active |
| Requires CREATE EXTENSION | Yes |
| Requires preload | No |
| Trusted | No |
| Relocatable | No |
| Stars | 7 |
| Latest commit | 2026-08-14 |
| Latest release | 2026-05-24 |
| Catalogue updated | 2026-08-30 |
| vector | vector data type and ivfflat and hnsw access methods |
| vector | vector data type and ivfflat and hnsw access methods |
| vectorize | The simplest way to do vector search on Postgres |
| pgturbohybrid | hybrid vector and BM25 search for PostgreSQL on top of pgvector |
| llama_embed | llama.cpp embedding extension for dense and multivector search |
| pg_colbert_llama | ColBERT embedding companion extension for pgturbohybrid |
| pgturbohybrid_experimental | experimental sparse and multivector features for pgturbohybrid |
| pgmnemo | Single-plan multimodal agent memory for PostgreSQL |
| pgcontext | Vector, filter-aware HNSW, and hybrid retrieval over authoritative PostgreSQL tables. |
| pg_deeplake | Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training. |
| pgedge_vectorizer | Asynchronous text chunking and embedding generation for PostgreSQL using background workers and pgvector. |
| rds_ai | Alibaba Cloud RDS extension for calling LLMs, generating embeddings, semantic retrieval, and end-to-end RAG from SQL |
| pg_semantic_cache | Caches query results and retrieves semantically similar results using pgvector embeddings and configurable eviction policies. |