Introducing the next generation of Amazon SageMaker
Today, AWS announces the next generation of Amazon SageMaker, a unified platform for data, analytics, and AI. This launch brings together widely adopted AWS machine learning and analytics capabilities and provides an integrated experience for analytics and AI with unified access to data and built-in governance. Teams can collaborate and build faster from a single development environment using familiar AWS tools for model development, generative AI application development, data processing, and SQL analytics, accelerated by Amazon Q Developer, the most capable generative AI assistant for software development.
The next generation of SageMaker also introduces new capabilities, including Amazon SageMaker Unified Studio (preview), Amazon SageMaker Lakehouse, and Amazon SageMaker Data and AI Governance. Within the new SageMaker Unified Studio, users can discover their data and put it to work using the best tool for the job across data and AI use cases. SageMaker Unified Studio brings together functionality and tools from the range of standalone studios, query editors, and visual tools available today in Amazon EMR, AWS Glue, Amazon Redshift, Amazon Bedrock, and the existing Amazon SageMaker Studio. SageMaker Lakehouse provides an open data architecture that reduces data silos and unifies data across Amazon Simple Storage Service (Amazon S3) data lakes, Amazon Redshift data warehouses, and third party and federated data sources. SageMaker Lakehouse offers the flexibility to access and query data with Apache Iceberg–compatible tools and engines. SageMaker Data and AI Governance, including Amazon SageMaker Catalog built on Amazon DataZone, empowers users to securely discover, govern, and collaborate on data and AI workflows.
For more information on AWS Regions where the next generation of Amazon SageMaker is available, see Supported Regions.
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