Search and analytics engine
OpenSearch Core is a distributed search and analytics engine built on Apache Lucene for indexing data, running searches, and analyzing results.
OpenSearch is a community-driven, Apache 2.0-licensed open source search and analytics suite for ingesting, searching, visualizing, and analyzing data. It supports application search, observability, security analytics, and machine learning workflows.
OpenSearch is an open source search and analytics suite built on Apache Lucene. It helps teams ingest, index, search, visualize, and analyze data through an integrated set of tools.
The platform combines OpenSearch Core, OpenSearch Dashboards, OpenSearch Data Prepper, and OpenSearch Vector Engine. Together, these components support application search, observability, security analytics, data preparation, vector search, and machine learning or generative AI workflows. OpenSearch is vendor-neutral and fully Apache 2.0 licensed from ingest to dashboard.
OpenSearch Core is a distributed search and analytics engine built on Apache Lucene for indexing data, running searches, and analyzing results.
OpenSearch Dashboards provides a flexible toolset for visually exploring and querying data through integrated visualizations.
OpenSearch Data Prepper collects data server-side and can filter, mutate, sample, enrich, transform, and aggregate it for downstream analytics.
OpenSearch Vector Engine is designed for vector-based machine learning and generative AI applications, with documented workflows for semantic, hybrid, conversational, and retrieval-augmented generation search.
The platform supports observability, performance monitoring, log analysis, security analytics, threat intelligence, event correlation, anomaly detection, and performance benchmarking.
Documentation covers installation with Docker, Helm, tarballs, RPM, Debian, Windows, and a Kubernetes Operator, along with cluster configuration, security, upgrades, snapshots, and replication.
Build search experiences for internal or application content by ingesting documents, indexing them, and querying the resulting collection through OpenSearch.
Collect and prepare operational data, then use search, dashboards, and analytics to investigate logs, monitor performance, and analyze application or infrastructure behavior.
Use indexed security data to support threat-intelligence analysis and event correlation as part of a security monitoring workflow.
Create vector, semantic, hybrid, conversational, or retrieval-augmented generation workflows using the documented vector-search and generative-AI capabilities.
Install and manage OpenSearch deployments using supported installation paths and documentation for cluster formation, configuration, upgrades, snapshots, and cross-cluster replication.
OpenSearch is used to ingest, index, search, visualize, and analyze data. The project highlights enterprise and document search, observability, log analysis, security analytics, vector search, anomaly detection, threat intelligence, and event correlation.
The site identifies OpenSearch Core, OpenSearch Dashboards, OpenSearch Data Prepper, and OpenSearch Vector Engine as platform components. Core provides search and analytics, Dashboards supports visual exploration, Data Prepper prepares data for analytics, and Vector Engine supports vector-oriented AI applications.
The documentation provides installation paths for Docker, Helm, tarballs, RPM, Debian, Windows, and a Kubernetes Operator. It also covers installing OpenSearch Dashboards and configuring clusters.
Yes. The documentation includes vector search, semantic and hybrid search, embeddings, reranking, conversational search, generative AI, retrieval-augmented generation, chatbots, and agentic AI workflows.
The homepage describes OpenSearch as community-driven, vendor-neutral, and fully Apache 2.0 licensed from ingest to dashboard. The provided sources do not specify paid plans, usage limits, or hosted-service pricing.
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