About the author
Benjamin Trent is a Lucene committer and member of the project management committee at The Apache Software Foundation and a software engineer at Elastic, where he works on improving Elasticsearch.
Author’s articles
August 27, 2024
Looking back: A timeline of vector search innovations
Looking back at Elastic's vector search innovations in Elasticsearch and Lucene
July 17, 2024
Bit vectors in Elasticsearch
Discover what are bit vectors, their practical implications and how to use them in Elasticsearch.
April 26, 2024
Making Elasticsearch and Lucene the best vector database: up to 8x faster and 32x efficient
Discover the recent enhancements and optimizations that notably improve vector search performance in Elasticsearch & Lucene vector database.
April 25, 2024
Understanding Int4 scalar quantization in Lucene
This blog explains how int4 quantization works in Lucene, how it lines up, and the benefits of using int4 quantization.
April 25, 2024
Scalar quantization optimized for vector databases
Optimizing scalar quantization for the vector database use case allows us to achieve significantly better performance for the same retrieval quality at high compression ratios.
December 7, 2023
Introducing kNN Query: An expert way to do kNN search
Explore how the kNN query in Elasticsearch can be used and how it differs from top-level kNN search, including examples.
November 11, 2023
Understanding scalar quantization in Lucene
Explore how Elastic introduced scalar quantization into Lucene, including automatic byte quantization, quantization per segment & performance insights.
October 25, 2023
Scalar quantization 101
Understand what scalar quantization is, how it works and its benefits. This guide also covers the math behind quantization and examples.
September 1, 2023
Bringing maximum-inner-product into Lucene
Explore how we brought maximum-inner-product into Lucene and the investigations undertaken to ensure its support.