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Amazon OpenSearch Service

Up to 750 hours per month on t2 and t3 small.search instances with the AWS Free Tier

Amazon OpenSearch Service

Simplify AI-powered search, observability, and vector database operations with a secure, cost-effective managed service.

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Introduction to OpenSearch Service

Amazon OpenSearch Service is an AWS-managed service that lets you run and scale OpenSearch clusters without having to worry about managing, monitoring, and maintaining your infrastructure, or having OpenSearch clusters operation expertise. OpenSearch is a distributed, community-driven, Apache 2.0-licensed, open-source search and analytics suite. OpenSearch Service reduces operational overhead, provides enterprise-grade security, high availability, and scalability, and enables you to quickly deploy real-time search, analytics, and generative AI applications. This helps organizations accelerate innovation and improve operational efficiency rather than managing infrastructure. You can choose between precise control with fully managed OpenSearch Service clusters or automatic resource optimization with Amazon OpenSearch Serverless to efficiently scale your vector workloads without incurring unnecessary costs.

Benefits of Amazon OpenSearch Service

Balance search quality, performance, and cost through flexible search options including traditional, vector-driven, and hybrid approaches. Users find relevant content through precise keyword matching or natural language queries, while administrators can tune search configurations to match specific use case requirements. Zero-ETL integrations with Amazon DynamoDB, Amazon DocumentDB, and Amazon S3, along with connections to other AWS services and databases, enable faster search implementation across your data sources while reducing storage costs and management overhead

Simplify generative AI implementation with an integrated vector database that manages billions of vectors efficiently. Rapidly develop generative AI applications through native integrations with Amazon Bedrock, Amazon SageMaker, Amazon Titan, and third-party models like OpenAI, Cohere, DeepSeek, and others through pre-built connectors.

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Analyze logs, traces, and metrics through unified dashboards. Direct query capabilities for Amazon S3, Amazon CloudWatch, and Amazon Security Lake eliminate data movement and reduce storage costs. Built-in machine learning detects anomalies and automates alerting for faster issue resolution.

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Choose between fully managed OpenSearch Service clusters for maximum control or OpenSearch Serverless collections for automated scaling. Managed clusters support up to 10PB hot data and an additional 15PB of warm data operations with custom configurations, while serverless eliminates operational complexity through automatic resource management. Both managed clusters and serverless options provide comprehensive security through encryption, index-level access controls, and Multi-AZ deployments for high availability, with managed clusters offering additional document-level security controls.

Features

AWS manages software installation, upgrades, and patching with 24x7 monitoring and automated self-healing, while supporting workloads that can scale up to 25 PB, 1,000 data nodes, and an additional 200 coordinator nodes. OpenSearch Service provides a single, proven technology that powers diverse workloads from search to analytics to vector database operations. The modern UI delivers comprehensive operational analytics through unified data analysis across multiple sources, with natural language queries and purpose-built workspaces for different use cases. OpenSearch is an Apache 2.0-licensed open-source solution, member of the Linux Foundation, and supported by AWS and a growing community to foster innovation and help organizations build advanced search experiences, implement AI capabilities, and derive operational insights with greater efficiency.

Managed OpenSearch

Run search workloads simply without the hassle of configuring, managing, and scaling OpenSearch clusters. OpenSearch Service provides the power of open-source search with interactive millisecond response times. Additionally, Amazon OpenSearch Serverless enables search and log analytics without provisioning and adjusting resources, automatically scaling resources based on your application's needs.

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Price performant and highly scalable vector database for generative AI applications

AWS recommends Amazon OpenSearch Service as the vector database for Amazon Bedrock. The integrated vector database powers modern generative AI applications through scalable vector storage and efficient search capabilities, enabling organizations to store and query billions of high-dimensional vector embeddings with millisecond response times. Organizations can integrate with foundation models on Amazon Bedrock, Amazon SageMaker, and third-party model providers like OpenAI, Cohere, and DeepSeek, combining vector search with traditional keyword queries to deliver more accurate, contextually relevant results. The solution supports Retrieval-Augmented Generation (RAG) applications and near real-time embedding updates, helping organizations build sophisticated generative AI experiences like semantic search, intelligent chatbots, and personalized recommendations while maintaining data accuracy. OpenSearch Serverless is also the default vector database for Amazon Bedrock Knowledge Bases. OpenSearch Serverless offers an auto-scaled, high-performing vector database that you can use to build with Amazon Bedrock for RAG and AI agents, without having to manage the vector database infrastructure.

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Fully managed data ingestion and transformation

Amazon OpenSearch Ingestion enables ingesting, transforming, and routing data at scale to OpenSearch domains and OpenSearch Serverless collections. OpenSearch Ingestion automatically scales to handle demanding workloads, reduces storage costs through deduplication and sampling, enforces data quality with built-in processors and schemas, protects sensitive data through redaction, and routes data based on compliance requirements.

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Comprehensive security for search and log analytics

Use robust security capabilities to audit and secure search and log analytics data, meeting requirements for authentication, authorization, encryption, audit trails, and regulatory compliance. OpenSearch Service offers granular access control, network isolation, secure programmatic access, compliance enablement across industry standards, and security analytics through log collection, normalization, and comparison.

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Integration with other AWS services

Simply integrate with other AWS services to deliver expanded search and analytics functionality. This includes seamless integration with Amazon DynamoDB and Amazon DocumentDB databases for advanced search on stored data, as well as frictionless search across Amazon Simple Storage Service (Amazon S3) to reduce the need for separate data indexing. You can now directly query and visualize Amazon CloudWatch Logs data in near real-time using Amazon OpenSearch Service without complex data pipelines or having to export or transform the data first. This zero ETL integration centralizes log data collection and storage, leveraging the scalable ingestion and storage of CloudWatch Logs along with the advanced analytics capabilities of OpenSearch Service. Zero ETL integration between Amazon Security Lake and Amazon OpenSearch Service, allows you to efficiently search and analyze voluminous security data that were previously cost-prohibitive to analyze without data integration challenges, streamlining security investigations and providing comprehensive visibility of your security landscape. The service further integrates with AWS model hosting services like Amazon Bedrock and Amazon SageMaker, enabling vector embeddings generation and storage, and AWS CloudTrail and AWS CloudWatch for enhanced cluster management and security auditing.

Download the solution brief

Visit our Features page for a full list of OpenSearch Service features and benefits.

Use cases

Centralize and analyze security and observability data for real-time threat detection, incident management, and improved application health, enhancing system visibility and customer experiences.

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Boost user engagement and conversions with the OpenSearch Service fast, personalized search. Quickly deliver relevant data across applications, websites, and data lake catalogs for an enhanced user experience.

Store and search billions of high-dimensional vectors efficiently for vector-driven search capabilities. Support generative AI applications with more accurate and contextually relevant results across multi-modal (text, image, audio, and video) data. Integrate with foundation models on Amazon Bedrock, Amazon SageMaker, and third-party model providers like OpenAI, Cohere, and DeepSeek to power sophisticated use cases like intelligent search, chatbots, personalized recommendations, anomaly detection, and AI-assisted analytics.

Enhance the accuracy and relevance of responses from large language models (LLMs) by incorporating Retrieval Augmented Generation (RAG) with OpenSearch Service as an external knowledge base.