vectorsearch
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How We Made 100M Vector Indexing in 20 Minutes Possible on PostgreSQL
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 …
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 …
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Introducing Vechord: Turn PostgreSQL into your search engine in a Pythonic way.
Today, we’re thrilled to announce the release of Vechord, a new Python library designed to dramatically simplify building robust search infrastructure directly on top of the PostgreSQL database. In the rapidly evolving world of AI and large language …
Today, we’re thrilled to announce the release of Vechord, a new Python library designed to dramatically simplify building robust search infrastructure directly on top of the PostgreSQL database. In the rapidly evolving world of AI and large language …
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Vector Search at 10,000 QPS in PostgreSQL with VectorChord
VectorChord is a PostgreSQL extension designed for scalable, high-performance, and disk-efficient vector similarity search, and serves as the successor to pgvecto.rs. In our previous blog post, we showed that with just $250 per month, VectorChord …
VectorChord is a PostgreSQL extension designed for scalable, high-performance, and disk-efficient vector similarity search, and serves as the successor to pgvecto.rs. In our previous blog post, we showed that with just $250 per month, VectorChord …
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Benefits and Steps of External Centroids Building in VectorChord
Clustering is an important component in vector search, and the k-means algorithm remains one of the most widely used techniques. However, its simplicity comes with a significant drawback: resource-intensive computation can render it impractical for …
Clustering is an important component in vector search, and the k-means algorithm remains one of the most widely used techniques. However, its simplicity comes with a significant drawback: resource-intensive computation can render it impractical for …
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pgvecto.rs 0.2: Unifying Relational Queries and Vector Search in PostgreSQL
We are excited to announce the release of pgvecto.rs 0.2, a significant milestone in the journey of bridging the gap between relational queries and vector search in PostgreSQL. This update brings together the power of both worlds, offering enhanced …
We are excited to announce the release of pgvecto.rs 0.2, a significant milestone in the journey of bridging the gap between relational queries and vector search in PostgreSQL. This update brings together the power of both worlds, offering enhanced …