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Amazon OpenSearch Service is trusted by organizations across all industries to power enterprise search, observability, and generative AI workloads. Customers value its fully managed capabilities, including automated scaling, patching, hardware provisioning, and 24x7 monitoring, allowing teams to focus on innovation rather than infrastructure management. It combines traditional and semantic search capabilities, powerful observability and log analytics features, and a high-performance vector database to enable generative and agentic AI.
Customers can achieve exceptional cost efficiency and performance at any scale, reducing the tradeoff between performance and affordability. OpenSearch Service supports a variety of deployment options, making it easy for organizations to start new cloud-based projects, migrate from self-managed environments, or undertake complete transitions to a managed service, with minimal disruption.
You can find more customer stories on our customer success story finder page and you 22read more technical content on our blog page. Visit our migration hub for comprehensive 23resources to simplify migration and improve performance.
Vector database and generative AI
Simplify generative AI implementation with an 29integrated vector database that manages billions of vectors efficiently. Rapidly develop 30generative AI applications through native integrations with Amazon Bedrock, Amazon 31SageMaker, Amazon Titan, and third-party models like OpenAI, Cohere, DeepSeek, and 32others through pre-built connectors.
Adobe needed to scale their Acrobat AI Assistant to serve hundreds of millions of users while providing accurate document attributions and multi-language support. By implementing Amazon OpenSearch Service for attribution citations and Amazon Bedrock Adobe needed to scale their Acrobat AI Assistant to serve hundreds of millions of users while providing accurate document attributions and multi-language support. By implementing Amazon OpenSearch Service for attribution citations and Amazon Bedrock for non-English language capabilities, Adobe successfully scaled their solution to help users quickly extract actionable insights from trillions of PDF documents.
Prime Video faced challenges in providing relevant sports search results for their growing catalog of live and on-demand sports content. By implementing Amazon OpenSearch Service with semantic search and AI/ML capabilities, powered by a custom text-embedding model on Amazon SageMaker, Prime Video significantly improved search relevance and precision, leading to increased customer engagement and content discovery for sports events.
DoorDash faced challenges in efficiently handling a high volume of calls from their contractor delivery workers, so they implemented a solution using Amazon Bedrock for foundation models, Amazon Bedrock Knowledge Bases to connect large language models to their data sources, and Amazon OpenSearch Serverless for scalable workloads. This serverless architecture enabled DoorDash to field hundreds of thousands of calls per day and significantly reducing the burden on live agents.
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
Audiense
This social media analytics provider faced performance challenges experiencing slow query times and weekly indexing that led to stale data. Their migration from Apache Solr to Amazon OpenSearch Service helped Audiense reduce query times by 1,400%, achieve near real-time indexing, and improve system reliability, enabling the company to deliver faster, more up-to-date insights to its customers.
MANZ, a leading Austrian legal information provider, needed to enhance its search capabilities for over 300 million legal documents. MANZ achieved average processing times of 200-300 milliseconds for searching 50 million documents by implementing Amazon OpenSearch Service with vector search capabilities. This solution improved search speed and accuracy and is expected to deliver up to 30% cost savings compared to their previous search solutions.
Juicebox, an AI-powered talent sourcing platform, needed to improve search capabilities across their database of over 800 million candidate profiles. Juicebox reduced query latency from 700 to 250 milliseconds, surfaced 35% more relevant candidates through semantic search, and enabled large-scale data aggregation queries that run on over 100 million profiles in under 800 milliseconds with Amazon OpenSearch Service.
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.
Netscout built an AWS solution on Amazon OpenSearch as an analytic engine for some of the services that we provide. So this gets threat intelligence to our customers for free.
Richard Hummel, Manager, Threat Intelligence - Netscout
Watch the video
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Amazon Video
Deliver seamless playback experience to more than 18 million football fans.
We collected a significant amount of data around quality of service, which is the experience viewers have on their devices. That information was sent to Amazon OpenSearch Service, and we used it to further optimize the overall playback experience in real-time.
BA Winston, Global Head of Digital Video Playback and Delivery - Amazon Video
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»
Hapag-Lloyd
Hapag-Lloyd's Web & Mobile team needed to monitor 20 cloud products comprising thousands of resources after migrating to AWS in 2020. They implemented Amazon OpenSearch Service for centralized logging and monitoring and successfully reduced troubleshooting time for its development teams and improved visibility into product performance across multiple AWS environments.
The ICCW needed to effectively monitor soil and water quality to investigate potential health issues in Indian villages. They implemented an AWS IoT solution with Amazon OpenSearch Service and can now analyze 90GB of sensor data daily with dashboard updates every two minutes. This enables them to track water quality changes in real-time and correlate findings with local health incidents to inform policy decisions.
Zurich Insurance Group needed to optimize their log management system while balancing storage costs and meeting long-term retention requirements across thousands of applications. Zurich successfully reduced SIEM data ingestion by 85%, projected a 53% cost reduction per GB of stored log data, and improved their ability to scale while maintaining compliance with retention requirements by implementing a hybrid solution using Amazon OpenSearch Service, Amazon S3, and other AWS services.
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.
