Modern applications rely on PostgreSQL for its fully ACID‑compliant, expressive SQL, and rich ecosystem of extensions. The database handles relational workloads exceptionally well, but many projects also need to search for large text collections—prod...| VectorChord
VectorChord 0.4 enhances PostgreSQL vector search, improving AI application latency and throughput with advanced I/O and prefiltering| VectorChord
Upload, index, and search 400M vectors with VectorChord and PostgreSQL. Includes hardware tips and search performance advice| VectorChord
Enhance generation in language models using PostgreSQL for contextual retrieval with vector search and keyword bm25 scoring.| VectorChord
Build production-ready RAG solutions in PostgreSQL with VectorChord Suite's vector search, BM25 ranking, and flexible tokenization extensions| VectorChord
Turn PostgreSQL into a powerful search engine with Vechord, a Python library for seamless vector and keyword search| VectorChord
Building effective Retrieval-Augmented Generation (RAG) systems for documents often feels like wrestling with messy, complex pipelines. Especially when dealing with PDFs or scanned images, traditional methods rely heavily on Optical Character Recogni...| VectorChord
VectorChord 0.3 boosts PostgreSQL vector search using MaxSim and WARP| VectorChord
Perform large-scale vector search in PostgreSQL with 3 billion+ vectors—powered by VectorChord. Get fast, scalable similarity search.| VectorChord
Vector Search in PostgreSQL: Comparing VectorChord, pgvector, and pgvectorscale for Memory and Disk Performance| VectorChord
We're excited to announce the release of VectorChord-BM25 version 0.2, our PostgreSQL extension designed to bring advanced BM25-based full-text search ranking capabilities directly into your database! VectorChord-BM25 allows you to leverage the power...| VectorChord
Boost PostgreSQL full-text search speed by 50x with simple optimizations. Use VectorChord-BM25 to accelerate and better BM25 ranking in postgres.| VectorChord
Hybrid search combining BM25 and pgvector compatible extension VectorChord, seamlessly integrated within PostgreSQL.| VectorChord
VectorChord, the successor to pgvecto.rs, is a PostgreSQL extension for vector search, scaling up to 10,000 QPS with ease.| VectorChord
VectorChord-BM25 enhances PostgreSQL search with BM25 ranking, 3x faster than ElasticSearch. Supports BERT, Tocken, and Unicode tokenizers| VectorChord
Notice: This article, originally published in 2023, discusses the relevance and necessity of specialized vector databases, particularly in relation to Postgres and its capabilities. For further insights and discussions on this topic, please refer to ...| VectorChord
VectorChord 0.2: Enhanced vector search in PostgreSQL with up to 60K dimensions, Float16 support, and faster ARM performance| VectorChord
ARM64 servers like AWS Graviton save costs. VectorChord - 26x cheaper than pgvector. Optimized for ARM64/x86, it delivers fast, efficient vector search| VectorChord
HNSW (Hierarchical Navigable Small World) has become the go-to algorithm for many vector databases. Its multi-layered graph structure and ability to efficiently navigate vector embeddings make it particularly appealing. However, despite its apparent ...| VectorChord
Enhance vector search efficiency with external centroids building in VectorChord using external resources and hierarchical K-means| VectorChord
Introducing VectorChord: The successor to pgvecto.rs. Using VectorChord, you can achieve a QPS of 131 with 0.95 precision on 100 million 768D dataset| VectorChord
Learn to enhance vector search accuracy with ColBERT rerank using PostgreSQL and VectorChord in this comprehensive tutorial| VectorChord
