Amazon Web Services outlined its next-generation Amazon SageMaker platform that will combine data, analytics and AI.

The move has multiple components, but in a nutshell AWS is tightly integrating data prep, integration, big data, SQL analytics, machine learning and generative AI. The headliner was SageMaker Lakehouse, which unifies data lakes, data warehouses, databases and enterprise applications and makes them available for queries.

Constellation Research analyst Doug Henschen said the SageMaker effort is notable.

"I was very impressed by AWS's SageMaker announcements at AWS re:invent2024. The new, unified SageMaker consolidates all data workloads and puts AI at center, where it belongs today. It builds on DataBricks' original, single-platform vision and goes further to consolidate and unify data work and workloads than Microsoft's moves with Fabric and Google Cloud's moves with BigQuery."

Here's a look at what was announced in addition to SageMaker Lakehouse:

  • SageMaker Unified Studio gives enterprises the ability to find and access data and combine it with AWS analytics, machine learning and AI tools. Amazon Q Developer is also integrated.
  • SageMaker Catalog has built-in governance.
  • SageMaker Lakehouse will enable data to be queried in SageMaker Unified Studio or query engines compatible with Apache Iceberg.
  • Zero-ETL integrations with various SaaS applications so data is available in SageMaker Lakehouse and Amazon Redshift without complex data pipelines.
  • SageMaker Unified Studio offers one interface to combine a bevy of AWS services currently in SageMaker.

AWS CEO Matt Garman said:

"Over the next year, we're going to be adding a ton new capabilities to the new SageMaker--capabilities like AutoML, new low code experiences, specialized AI service integration, stream processing and search and access to more services and data in a single unified UI."

Constellation Research analyst Holger Mueller said:

"It is not long ago when former AWS CEO, now Amazon CEO, would say that large product suites and offerings would slow down innovation and this hurt customers. The upside though is that it is a reduction of complexity for enterprises for data and AI. AWS decided to merge the data and AI services into a single platform, rightfully picking the higher level offering with SageMaker as the new brand. The big news apart from the bundling is the new Lakehouse underpinning the new Amazon SageMaker Studio."

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