
Elasticsearch: The Official Distributed Search & Analytics Engine | Elastic
Elasticsearch is the leading distributed, RESTful, open source search and analytics engine designed for speed, horizontal scalability, reliability, and easy management.
Download Elasticsearch | Elastic
Download Elasticsearch or the complete Elastic Stack (formerly ELK stack) for free and start searching and analyzing in minutes with Elastic.
Elastic Docs
Solutions and use cases Elasticsearch Build powerful search and RAG applications using Elasticsearch's vector database, AI toolkit, and advanced retrieval capabilities.
Elastic — The Search AI Company
Effortless Elasticsearch management — AutoOps is here, and it's free for Elastic Cloud customers. Read the blog
Elastic fundamentals | Elastic Docs
Manage data: Learn how to ingest and manage data stored in Elasticsearch. How to use the documentation: Understand how our documentation is organized, find the right version information …
Download and provision Elastic Products
Download Elasticsearch to get started with search, observability, and security for free. Deploy on Elastic Cloud (hosted or serverless), run it yourself on-premises, or use our official Kubernetes operator.
Elasticsearch:官方分布式搜索和分析引擎 | Elastic
Elasticsearch powers observability solutions with scalable data ingestion, fast search, and advanced analytics — helping teams detect issues, troubleshoot performance, and optimize system health …
Elastic Stack: (ELK) Elasticsearch, Kibana & Logstash
It's comprised of Elasticsearch, Kibana, Beats, and Logstash (also known as the ELK Stack) and more. Reliably and securely take data from any source, in any format, then search, analyze, and visualize.
Elastic Docs | Elastic
Free Elastic training Learn about Elasticsearch Relevance Engine™ (ESRE), designed to power AI search applications.
Deploy an Elasticsearch cluster | Elastic Docs
In production, we recommend you run Elasticsearch on a dedicated host or as a primary service. Several Elasticsearch features, such as automatic JVM heap sizing, assume that Elasticsearch is the …