Tiger Data 开源 pg_vectorsearch：为 PostgreSQL 带来更可扩展的向量搜索
原标题：Open Source pg_vectorsearch Brings More Scalable Vector Search to PostgreSQL
AI 摘要
Tiger Data 发布开源 PostgreSQL 扩展 pg_vectorsearch（alpha 版），其 PRISM 索引采用分区与压缩而非图结构，在 1 亿向量基准中建索引耗时 1 小时 40 分、内存 128GB，而 pgvector 的 HNSW 需 42 小时、512GB。该扩展兼容现有 pgvector 列，可减少独立向量库的基础设施需求，但增量重平衡与过滤搜索尚未实现，社区对独立基准验证持谨慎态度。Tiger Data 计划将 pgvectorscale 转入维护模式。
正文节选
Tiger Data has released pg_vectorsearch, an open source PostgreSQL extension for vector similarity search, currently in alpha. Its PRISM index uses data partitioning and compression instead of the graph-based approach used by pgvector’s HNSW index, reducing memory requirements and index build times. According to the authors, pg_vectorsearch enables faster, more memory-efficient vector search directly in PostgreSQL, reducing the infrastructure required to handle large vector datasets. The extensi