Elasticsearch Labs Blog
RBAC and RAG - Best Friends
Dive into the dynamic duo of RAG and RBAC. Discover how they team up to supercharge AI capabilities while ensuring your data stays under lock and key; an essential read for navigating the thrilling intersection of AI and data protection.
Red Hat extends collaboration with Elasticsearch vector database for Red Hat OpenShift AI
Elasticsearch is now a preferred vector database solution on Red Hat OpenShift AI
Evaluating scalar quantization in Elasticsearch
Learn how scalar quantization can be used to reduce the memory footprint of vector embeddings in Elasticsearch.
ES|QL queries to Java objects
How perform ES|QL queries with the Java client
Making Elasticsearch and Lucene the best vector database: up to 8x faster and 32x efficient
Recent features bring significant performance gains to Elasticsearch and Lucene vector database.
Elastic Cloud adds Elasticsearch Vector Database optimized instance to Google Cloud
Elasticsearch adds a new vector search optimized profile for GCP.
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.
Int4: More Scalar Quantization in Lucene
Optimizing scalar quantization in Lucene and adding int4 support.
Making Lucene Faster with Vectorization and FFI/madvise
Moving Lucene forward with modern Java features