Amazon SageMaker Unified Studio is in preview release and is subject to change.
Amazon SageMaker Lakehouse
Amazon SageMaker Lakehouse unifies your data across Amazon S3 data lakes and Amazon Redshift data warehouses, helping you
build powerful analytics, machine learning (ML), and generative AI applications on a single copy
of data. Amazon SageMaker Lakehouse provides integrated access controls and open-source Apache Iceberg
Amazon SageMaker Lakehouse provides the following key capabilities.
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Unified data access - Amazon SageMaker Lakehouse lets you query and access data across Amazon S3 data lakes, Amazon Redshift data warehouses, and other sources using Apache Iceberg
compatible tools and engines. This includes AWS services such as Amazon Athena, Amazon Redshift, Amazon EMR, Amazon SageMaker, as well as third-party engines, all of which you can use to query your data in-place. -
Integrated access control - Amazon SageMaker Lakehouse provides integrated fine-grained access control to your data. This allows you to define permissions and consistently apply them across all analytics and ML tools and engines, regardless of the underlying storage formats or query engines used.
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Open source compatibility - Amazon SageMaker Lakehouse leverages open-source Apache Iceberg
, enabling data interoperability across various Apache Iceberg compatible query engines and tools. This gives you the flexibility to choose your preferred tools and engines.
In this chapter:
