OpenSearch is a community-driven open source search and analytics suite that developers use to ingest, search, visualize, and analyze data. OpenSearch consists of data storage and search engine (OpenSearch), visualization and user interface (OpenSearch Dashboards), and server-side data collector (Data Prepper). Users can extend OpenSearch's capabilities with a range of plug-ins that enhance search, analytics, observability, security, machine learning, and more.
The OpenSearch project was first announced in January 2021 as an open source fork of Elasticsearch and Kibana, aiming to provide a secure, high-quality, fully open source search and analysis suite with a rich feature roadmap. In July 2021 , the project released OpenSearch 1.0 for production under the Apache License Version 2.0 (ALv2), and the code base has been published to GitHub and is open for contributions from the OpenSearch community. A comprehensive project roadmap is maintained here .
Since the project's inception, the OpenSearch community has grown to over 100 contributors, thousands of pull requests, thousands of issues resolved, and organized in over 90 repositories. In November 2022, OpenSearch released version 2.4 of the project , which introduced the Windows distribution and enhanced cluster resiliency, search capabilities, analysis tools, etc.
As a fully open source solution, OpenSearch gives you the freedom to modify, extend, monetize and resell the product as you see fit, as well as the flexibility to deploy on a variety of infrastructures. At the same time, the OpenSearch project provides a secure, high-quality search and analytics suite with a rich roadmap of new and innovative features.
Build powerful search solutions
Deploy e-commerce, applications, and document search using community-built tools. Power artificial intelligence (AI) applications using OpenSearch's vector database capabilities . Support for full-text queries , natural language processing, custom dictionaries and a range of search capabilities provide a flexible foundation for structured and unstructured search applications. With built-in faceting, relevance ranking and scoring, and a range of machine learning (ML) capabilities, you can build search solutions fine-tuned for your data.
Analysis and discovery at scale
Capture, store and analyze your business, operational and security data from a variety of sources. Use your preferred data collector and enrich your analysis pipeline with integrated ML tools such as anomaly detection . Built-in search capabilities enable fast, accurate query results and time-sensitive insights. Visualize and report findings using OpenSearch dashboards and connect to popular business intelligence systems using JDBC .
Enable end-to-end observability
Use flexible observability tools to visualize your monitored environment from start to finish and identify and resolve issues as they arise. Build visualizations from your metrics, traces, and logs, and optionally use Data Prepper to transform and enrich your source data. Support for open source systems like OpenTelemetry and Prometheus means you can create powerful custom observability solutions using state-of-the-art components.
Basic introduction
OpenSearch includes a data storage and search engine, a visualization and user interface, and a library of plug-ins that you can use to customize your tool to your requirements. Start with what works best for your team and environment. To configure your first OpenSearch cluster, you can download OpenSearch components from various distributions or start from the official Docker Image .