1. Introduction In the past few months, we’ve heard consistent feedback from users and partners: while our goal of providing a scalable, high-performance alternative to pgvector is well-received, index build time and memory usage remain major concern...
We're excited to announce the release of VectorChord 0.4, a significant update that enhances high-performance vector search within PostgreSQL. We believe this release pushes the boundaries of what's possible for vector search in PostgreSQL, introduci...
Introduction: real-world challenges Specialized vector databases aren’t always needed. With PostgreSQL extensions like pgvector, pgvectorscale, VectorChord (which evolved from pgvecto.rs), you get vector search plus relational power—no extra infras...
You might have come across discussions or blog posts suggesting that PostgreSQL's built-in full-text search (FTS) struggles with performance compared to dedicated search engines or specialized extensions. A notable recent example comes from Neon's bl...
Traditional vector search methods typically employ sentence embeddings to locate similar content. However, generating sentence embeddings through pooling token embeddings can potentially sacrifice fine-grained details present at the token level. ColB...