Generate SPLADE sparse-vector embeddings inside PostgreSQL
pgext.cloud · Source code · Documentation · Control file
| Package | pg_splade |
|---|---|
| Version | 0.0.0 |
| PostgreSQL versions | 12 · 13 · 14 · 15 · 16 · 17 |
| Repository | Unspecified |
| Extension type | Preloaded |
| Project status | Active |
| Requires CREATE EXTENSION | Yes |
| Requires preload | Yes |
| Trusted | No |
| Relocatable | Yes |
| Shared libraries | pg_splade |
| Stars | 1 |
| Latest commit | 2025-04-16 |
| 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 |
| pgcontext | Vector, filter-aware HNSW, and hybrid retrieval over authoritative PostgreSQL tables. |
| vectorize | The simplest way to do vector search on Postgres |
| pg_bestmatch | Generate BM25 sparse vector inside PostgreSQL |
| pgmnemo | Single-plan multimodal agent memory for PostgreSQL |
| flame | PGRX proof-of-concept extension that generates text embeddings with fastembed/MiniLM. |
| sparse_vector | C data type and functions for sparse float vectors, normalization, dot product, and cosine similarity. |
| pg_similarity | support similarity queries |
| smlar | Effective similarity search |
| rds_embedding | Alibaba Cloud RDS text-to-vector model invocation extension |