VectorChord cuts PostgreSQL vector indexing time from 40 hours to 20 minutes for 100M vectors, reducing memory from 200GB to 12GB via hierarchical K-means, dimensionality reduction, and parallel processing optimizations.

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 concerns at billion-scale. Now VectorChord can index 100 million 768-dimensional vectors in 20 minutes on a 16 vCPU machine with just 12 GB of memory. By contrast, indexing the same data with pgvector requires around 200 GB of memory and about 40 hours on a...