Blogs
Developer insights and practical how-to articles from our experts to inspire and empower your search experience.
Red Hat & Elastic: Red Hat OpenShift AI integration with Elasticsearch
Red Hat OpenShift users can now implement Elasticsearch for vector search & RAG applications via the Red Hat Ecosystem Catalog. Explore this integration here.
Evaluating scalar quantization in Elasticsearch
Learn how scalar quantization can be used to reduce the memory footprint of vector embeddings in Elasticsearch through an experiment.
ES|QL queries to Java objects
Learn how to perform ES|QL queries with the Java client. Follow this guide for step-by-step instructions, including examples.
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.
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.
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.
Elastic Cloud adds Elasticsearch Vector Database optimized instance to Google Cloud
Elasticsearch's vector search optimized profile for GCP is available. Learn more about it and how to use it in this blog.
Simplifying kNN search
Elastic's kNN search has evolved. This blog explains the simplification of kNN search, where k and num_candidates are now optional.
Making Lucene faster with vectorization and FFI/madvise
Discover how modern Java features, including vectorization and FFI/madvise, are speeding up Lucene's performance.
Elasticsearch .NET client evolution: From NEST to Elastic.Clients.Elasticsearch
Learn about the evolution of the Elasticsearch .NET client and the transition from NEST to Elastic.Clients.Elasticsearch.
Elastic web crawler: Add search to your website
Learn through an example how to leverage the Elastic Web Crawler to crawl a website, ingest its content & prepare the data for search.
