글 Gilad Gal
Principal Product Manager I, Elastic
Elastic Stack 8.12: Enhanced vector search with improvements to ES|QL and more
The 8.12 release includes improved vector data handling with efficient search, query parallelization, enhanced pipeline features, remote search status, new maintenance windows, and ES|QL query editing in Dashboard.
Elastic Stack 8.11: Introducing a new powerful query language, ES|QL
Elastic Stack 8.11 introduces an advanced query language known as ES|QL in the Discover application, making data exploration more straightforward and user friendly. The Elastic Learned Sparse EncodeR (ELSER) is now generally available.
Elastic Stack 8.10: Simpler cross-cluster search and authentication, and more
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: Hybrid search with RRF, faster vector search, and public-facing search endpoints
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.
Introducing Elastic Learned Sparse Encoder: Elastic’s AI model for semantic search
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 시작하기
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.