Databricks
Unified data and AI platform for engineering, analytics, machine learning and governed AI agents on open lakehouse architecture.
AI Research & Data ToolsFreemium
AI Agent Builders Tools
- Introduction
- Integrated AWS platform to build, train, and deploy ML models and foundation models, with unified data, analytics, and SQL access.
- Added on
- 10/29/2026
- Pricing
- Paid
- Official links
- Website, company & support ↗
PRODUCT OVERVIEW
What is Amazon SageMaker?
Amazon SageMaker is the next generation of AWS's machine learning platform, bringing together ML and analytics capabilities in an integrated experience with unified access to data. Through SageMaker AI, teams can build, train, and deploy models, including foundation models, using fully managed infrastructure, tools, and workflows such as HyperPod, JumpStart, and MLOps. SageMaker Unified Studio provides a single development environment for model development, generative AI, data processing, and SQL analytics, accelerated by Amazon Q Developer. SageMaker Catalog adds governance and collaboration, while SageMaker Lakehouse unifies access across Amazon S3 data lakes, Amazon Redshift warehouses, and third-party or federated sources. It targets data scientists, developers, and enterprises needing governed, scalable AI and analytics workflows. Access is through AWS with pay-as-you-go pricing.
How to use Amazon SageMaker
- 1
Create an AWS account
Sign up for an AWS account to access Amazon SageMaker and related AWS services.
- 2
Open SageMaker Unified Studio
Use the unified development environment to work with data, analytics, and AI tools in one place.
- 3
Build and train models
Use SageMaker AI tools such as JumpStart and HyperPod to develop and train ML models, including foundation models.
- 4
Deploy and govern
Deploy models with managed infrastructure and use SageMaker Catalog to govern and collaborate on data and AI assets.
Amazon SageMaker Features
Build, train, and deploy ML models, including foundation models, with fully managed infrastructure
SageMaker Unified Studio for model development, generative AI, data processing, and SQL analytics
SageMaker AI tools including HyperPod, JumpStart, and MLOps
SageMaker Catalog for secure discovery, governance, and collaboration on data and AI
SageMaker Lakehouse unifies access across S3 data lakes, Redshift warehouses, and federated sources
Accelerated by Amazon Q Developer
Amazon SageMaker Use Cases
Training and deploying machine learning models at scale
Building and customizing generative AI and foundation model applications
Running SQL analytics alongside AI development in one environment
Governing and collaborating on data and AI assets across teams
Amazon SageMaker FAQs
It is AWS's integrated platform for data, analytics, and AI, combining ML development, generative AI, data processing, and SQL analytics with unified data access.
SageMaker AI includes tools such as HyperPod, JumpStart, and MLOps for building, training, and deploying models with managed infrastructure.
It is a single development environment for building with data and tools for analytics and AI, accelerated by Amazon Q Developer.
SageMaker Catalog, built on Amazon DataZone, lets teams securely discover, govern, and collaborate on data and AI assets.
It unifies data access across Amazon S3 data lakes, Amazon Redshift data warehouses, and third-party or federated data sources.
AWS generally uses pay-as-you-go pricing, paying only for the services consumed without long-term contracts. Specific SageMaker rates are on the SageMaker pricing page.
Yes, the AWS Pricing Calculator lets you estimate individual or multiple prices and model complete solutions.
AWS documentation is available at docs.aws.amazon.com, covering SageMaker and other AWS services.
Amazon SageMaker Official Information
- Company
- Amazon Web Services
- Website
- https://aws.amazon.com/sagemaker
- Documentation
- https://docs.aws.amazon.com/
- Contact
- https://aws.amazon.com/contact-us/
Amazon SageMaker Pricing
AWS uses pay-as-you-go pricing for most services, with no long-term contracts required. Specific SageMaker rates are listed on the SageMaker pricing page and can be estimated with the AWS Pricing Calculator.
See the official website for current pricing.
COMMUNITY REVIEWS
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