Amazon SageMaker Lakehouse
Simplify analytics and AI with a unified, open, and secure data lakehouse
What is SageMaker Lakehouse?
Amazon SageMaker Lakehouse unifies all your data across Amazon Simple Storage Service (Amazon S3) data lakes, including S3 Tables, and Amazon Redshift data warehouses, helping you build powerful analytics and AI/ML applications on a single copy of data. SageMaker Lakehouse gives you the flexibility to access and query your data in-place with all Apache Iceberg–compatible tools and engines. Secure your data in the lakehouse by defining fine-grained permissions that are enforced across all analytics and machine learning (ML) tools and engines. Bring data from operational databases and applications into your lakehouse in near real time through zero-ETL integrations. Additionally, access and query data in-place with federated query capabilities across third-party data sources.
See it in action
See how you can access unified data from S3 data lakes, S3 Tables, and Redshift data warehouses in SageMaker Lakehouse.
Benefits
Use cases
Customers
Lennar
"We have spent the last 18 months working with AWS to transform our data foundation to use best-in-class solutions that are cost effective as well. With advancements like Amazon SageMaker Unified Studio and Amazon SageMaker Lakehouse, we are accelerating our velocity of delivery through seamless access to data and services, thus enabling our engineers, analysts, and scientists to surface insights that provide material value to our business."
Lee Slezak, SVP of Data and Analytic, Lennar
Roche
Roche is a global pioneer in pharmaceuticals and diagnostics focused on advancing science to improve people's lives.
“We have been using Amazon Redshift to gain insights from both structured and semistructured data across all our data repositories. The new Amazon SageMaker Lakehouse excites me with its potential to enhance and unify access to data lakes or other data sources with services like Amazon Redshift, AWS Glue Data Catalog, and AWS Lake Formation. This innovation will allow our data and engineering teams to simplify data access, promoting interoperability across data, analytics, and application workloads. I foresee a notable reduction in data errors through less data copying, a 40% decrease in processing time, quicker analytics data write-back to transactional systems for improved decision-making, and empowering our teams to focus on creating business value.”
Yannick Misteli, Head of Engineering, Global Product Strategy, Roche
Idealista
Idealista supports real estate agents and private individuals across Southern Europe by providing an online real estate classifieds platform.
“Our goal is to streamline access to Salesforce data for enhanced analytics in our data lake. By leveraging the new Amazon SageMaker Lakehouse support for zero-ETL integrations from applications feature, we can simplify our data extraction and ingestion processes, removing the need for multiple ETLs to access Salesforce directly. This centralized approach reduces complexity and significantly improves our data management efficiency. We anticipate a significant time savings in data extraction and ingestion development, allowing our team to focus on deriving actionable insights from our data rather than managing its collection.“
Javier Monterrubio, Data Platform Engineer Manager, Idealista
Carrier
"At Carrier, the next generation of Amazon SageMaker is transforming our enterprise data strategy by streamlining how we build and scale data products. SageMaker Unified Studio’s approach to data discovery, processing, and model development has significantly accelerated our lakehouse implementation. Most impressively, its seamless integration with our existing data catalog and built-in governance controls enables us to democratize data access while maintaining security standards, helping our teams rapidly deliver advanced analytics and AI solutions across the enterprise."
Partners
Tableau
Tableau helps people and organizations become more data-driven.
“The partnership between Amazon and Salesforce Tableau represents a shared commitment to innovation and customer success. Through Amazon’s new zero-ETL integration, we are combining Tableau’s AI-powered data and analytics with Amazon’s powerful data infrastructure to transform how organizations gain insight from their data. This seamless integration enables our customers to get insights from all of their structured and unstructured data using the power of Amazon SageMaker Lakehouse and Amazon Redshift, dramatically reducing engineering complexity and deployment time. Together, Tableau and Amazon are helping customers accelerate digital transformation and drive business value at scale.“
Ali Tore, Senior VP, Advanced Analytics, Tableau
dbt Labs
dbt Labs is on a mission to help analysts create and disseminate organizational knowledge.
"We've long been the transformation standard on top of Amazon Redshift, offering flexibility, collaboration, and trust. With the new Amazon SageMaker Lakehouse, we're excited to extend this value to more customers and even more data in the AWS environment. Now, customers can access all their data across the AWS system, including data warehouses and data lakes. We're excited to join our capabilities with the new Amazon SageMaker to deliver governance, cataloging, and data optimizations for our joint customers.”
Shawn Toldo, VP Partnerships, dbt Labs
Informatica
Informatica, a leader in enterprise AI–powered cloud data management, brings data and AI to life by empowering businesses to realize the transformative power of their most critical assets.
“Our Intelligent Data Management Cloud (IDMC) platform and Amazon SageMaker help organizations unlock data potential and drive innovation and efficiency. As an Amazon SageMaker Lakehouse launch partner, we're proud to deliver an enterprise-grade solution that meets the high standards of modern data-driven organizations. Together with AWS's infrastructure, we enable faster, informed decisions for impactful outcomes across industries.”
Pratik Parekh, SVP Product Management, Informatica
