Elasticsearch Labs Blog
Retro relevance: Balancing keyword and semantic search
Highlights from a Haystack 2024 talk on balancing keyword and semantic search, saving time and effort for better relevance
Vector similarity techniques and scoring
Learn about all the similarity functions supported by Elasticsearch to compare vectors
Retrieval of originating information in multi-vector documents
Learn more on how to link original context to a multi-vector document.
How to detect which index template Elasticsearch will use before an index creation
Learn how to detect which index template Elasticsearch will use before creating the index itself.
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.