5 Integrations with AWS HealthLake
View a list of AWS HealthLake integrations and software that integrates with AWS HealthLake below. Compare the best AWS HealthLake integrations as well as features, ratings, user reviews, and pricing of software that integrates with AWS HealthLake. Here are the current AWS HealthLake integrations in 2026:
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Amazon Web Services (AWS)
Amazon
Amazon Web Services (AWS) is the world’s most comprehensive cloud platform, trusted by millions of customers across industries. From startups to global enterprises and government agencies, AWS provides on-demand solutions for compute, storage, networking, AI, analytics, and more. The platform empowers organizations to innovate faster, reduce costs, and scale globally with unmatched flexibility and reliability. With services like Amazon EC2 for compute, Amazon S3 for storage, SageMaker for AI/ML, and CloudFront for content delivery, AWS covers nearly every business and technical need. Its global infrastructure spans 120 availability zones across 38 regions, ensuring resilience, compliance, and security. Backed by the largest community of customers, partners, and developers, AWS continues to lead the cloud industry in innovation and operational expertise. -
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Amazon Athena
Amazon
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run. Athena is easy to use. Simply point to your data in Amazon S3, define the schema, and start querying using standard SQL. Most results are delivered within seconds. With Athena, there’s no need for complex ETL jobs to prepare your data for analysis. This makes it easy for anyone with SQL skills to quickly analyze large-scale datasets. Athena is out-of-the-box integrated with AWS Glue Data Catalog, allowing you to create a unified metadata repository across various services, crawl data sources to discover schemas and populate your Catalog with new and modified table and partition definitions, and maintain schema versioning. -
3
Amazon SageMaker
Amazon
Amazon SageMaker is an advanced machine learning service that provides an integrated environment for building, training, and deploying machine learning (ML) models. It combines tools for model development, data processing, and AI capabilities in a unified studio, enabling users to collaborate and work faster. SageMaker supports various data sources, such as Amazon S3 data lakes and Amazon Redshift data warehouses, while ensuring enterprise security and governance through its built-in features. The service also offers tools for generative AI applications, making it easier for users to customize and scale AI use cases. SageMaker’s architecture simplifies the AI lifecycle, from data discovery to model deployment, providing a seamless experience for developers. -
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Amazon QuickSight
Amazon
Amazon QuickSight allows everyone in your organization to understand your data by asking questions in natural language, exploring through interactive dashboards, or automatically looking for patterns and outliers powered by machine learning. QuickSight powers millions of dashboard views weekly for customers such as the NFL, Expedia, Volvo, Thomson Reuters, Best Western and Comcast, allowing their end-users to make better data-driven decisions. Ask conversational questions of your data and use Q’s ML-powered engine to receive relevant visualizations without the time-consuming data preparation from authors and admins. Discover hidden insights from your data, perform accurate forecasting and what-if analysis, or add easy-to-understand natural language narratives to dashboards by leveraging AWS' expertise in machine learning. Easily embed interactive visualizations and dashboards, sophisticated dashboard authoring, or natural language query capabilities in your applications. -
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AWS AI Services
Amazon
AWS pre-trained AI Services provide ready-made intelligence for your applications and workflows. AI Services easily integrate with your applications to address common use cases such as personalized recommendations, modernizing your contact center, improving safety and security, and increasing customer engagement. Because we use the same deep learning technology that powers Amazon.com and our ML Services, you get quality and accuracy from continuously-learning APIs. And best of all, AI Services on AWS doesn't require machine learning experience. Catalog assets, automate workflows, and extract meaning from your media and applications. Identify missing product components, vehicle and structure damage, and irregularities for comprehensive quality control. Improve operations with automated monitoring to find bottlenecks and assess manufacturing quality and safety. Pull valuable information from millions of documents at speed.
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