Simplify configuring cross-cluster search, execute vector search faster, detect data drifts and log rate dips, stream Elastic Agent to Kafka, and authenticate Webhook connector using third-party security certificates with Elastic Stack 8.10.

Elastic Search 8.9 brings improvements to vector search and ingestion and presents hybrid search with RRF to combine vector, keyword, and semantic techniques. Public-facing search endpoints for indices are now available with search applications beta.

Elastic Stack 8.9 delivers significant speed-up of aggregations for metrics, faster and more reliable cross-cluster searches, and management of alert rules using Terraform.

Elastic Learned Sparse Encoder is an AI model for high relevance semantic search across domains. As a sparse vector model, it expands the query with terms that don't exist in the query itself, delivering superior relevance without domain adaptation.

Elastic에서 구현한 읽기 스키마인 런타임 필드 소개 이제 성능을 위해 쓰기 스키마를 사용하거나 유연성을 위해 읽기 스키마를 사용할 수 있습니다. 이 블로그에서는 런타임 필드를 시작하는 방법을 설명합니다.

Elasticsearch 7.2.0 is here! Learn about our new proximity ranking (geo and time), enhancements to SQL, and support for OpenID Connect.