This version of the OpenSearch documentation is no longer maintained. For the latest version, see the current documentation. For information about OpenSearch version maintenance, see Release Schedule and Maintenance Policy.
Why use OpenSearch?
OpenSearch is well-suited to the following use cases:
- Log analytics
- Real-time application monitoring
- Clickstream analytics
- Search backend
|OpenSearch||Data store and search engine|
|OpenSearch Dashboards||Search frontend and visualizations|
|Security||Authentication and access control for your cluster|
|Alerting||Receive notifications when your data meets certain conditions|
|SQL||Use SQL or a piped processing language to query your data|
|Index State Management||Automate index operations|
|KNN||Find “nearest neighbors” in your vector data|
|Performance Analyzer||Monitor and optimize your cluster|
|Anomaly detection||Identify atypical data and receive automatic notifications|
|ML Commons plugin||Train and execute machine-learning models|
|Asynchronous search||Run search requests in the background|
|Cross-cluster replication||Replicate your data across multiple OpenSearch clusters|
Most OpenSearch plugins have corresponding OpenSearch Dashboards plugins that provide a convenient, unified user interface.
For specifics around the project, see the FAQ.
The secure path forward
OpenSearch includes a demo configuration so that you can get up and running quickly, but before using OpenSearch in a production environment, you must configure the security plugin manually with your own certificates, authentication method, users, and passwords.
Looking for the Javadoc?
The project welcomes GitHub issues, bug fixes, features, plugins, documentation—anything at all. To get involved, see Contributing on the OpenSearch website.
OpenSearch includes certain Apache-licensed Elasticsearch code from Elasticsearch B.V. and other source code. Elasticsearch B.V. is not the source of that other source code. ELASTICSEARCH is a registered trademark of Elasticsearch B.V.