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Amazon SageMaker Unified Studio - Unified Data and AI

Amazon SageMaker Unified Studio unifies AWS data, analytics, AI and ML tools in one development environment for collaborative projects.

Machine Learning
Pricing Model Consumption-based (no separate charge for Unified Studio)
Availability Multiple regions incl. EU (Ireland, Frankfurt, London, Paris, Stockholm)
Data Sovereignty EU regions available
Reliability N/A (SLAs of the underlying AWS services apply) SLA

What is Amazon SageMaker Unified Studio?

Amazon SageMaker Unified Studio is a unified, web-based development environment that brings AWS data, analytics, AI and ML services together in a single interface. Instead of switching between separate consoles and tools, teams build, deploy, run and monitor their workflows in one place. To do this, Unified Studio integrates Amazon EMR, AWS Glue, Amazon Athena, Amazon Redshift, Amazon Bedrock and Amazon SageMaker AI, plus SageMaker Lakehouse for unified data access and SageMaker Catalog for governance.

The product addresses the fragmentation that arises in many data and AI initiatives when data engineering, analytics and data science work in different tools. Administrators set up domains and manage users and groups through SSO or IAM. Within shared projects, teams create and share data, computation work and other resources under consistent access control. Amazon SageMaker Unified Studio therefore supports collaborative data and AI work from data preparation through to a production model.

Core features

  • Unified development environment: A single web-based interface bundles AWS data, analytics, AI and ML tools so teams build, run and monitor workflows centrally.
  • Integrated AWS services: Native connectivity to Amazon EMR, AWS Glue, Amazon Athena, Amazon Redshift, Amazon Bedrock and Amazon SageMaker AI, complemented by SageMaker Lakehouse for data access and SageMaker Catalog for governance.
  • Project-based collaboration: Administrators create domains and manage access through SSO or IAM. Teams share data, code and resources in shared projects.
  • Generative AI assistance: Amazon Q Developer helps with natural-language SQL, ETL job creation, troubleshooting and code suggestions. Amazon Bedrock provides Knowledge Bases, Guardrails, Agents and Flows.

Typical use cases

Cross-team data and ML projects: Data engineers, analysts and data scientists work in one shared project. They share data sources, notebooks and models in a single interface, without tool breaks and with consistent access control.

Data preparation and analytics: Teams build ETL pipelines with AWS Glue and Amazon EMR, run ad hoc queries through Amazon Athena and analyze data on Amazon Redshift and SageMaker Lakehouse, all from the same environment.

Prototyping generative AI: Through Amazon Bedrock, teams prototype GenAI applications with Knowledge Bases, Guardrails, Agents and Flows. Amazon Q Developer speeds up recurring development tasks.

Benefits

  • One interface instead of many separate tools reduces context switching and onboarding effort
  • Shared projects and central governance through SageMaker Catalog ease collaboration
  • Consumption-based billing with no separate charge for Unified Studio and no upfront commitment
  • EU regions enable processing and storing data within the EU

Integration with innFactory

As an AWS Reseller, innFactory supports you with the adoption and operation of this service.

Typical Use Cases

Cross-team data and ML projects in a single interface
ETL and data preparation with Glue, EMR and Athena
Analytics on Redshift and SageMaker Lakehouse
Prototyping generative AI applications with Amazon Bedrock

Frequently Asked Questions

What is Amazon SageMaker Unified Studio?

Amazon SageMaker Unified Studio is a unified, web-based development environment that brings AWS data, analytics, AI and ML services together in one interface. It integrates Amazon EMR, AWS Glue, Amazon Athena, Amazon Redshift, Amazon Bedrock and Amazon SageMaker AI, among others. Teams use it to build, share and operate data and AI workflows in shared projects.

When should I use Amazon SageMaker Unified Studio?

Use Unified Studio when multiple teams from data engineering, analytics and data science collaborate in shared projects and currently switch between separate tools. Typical scenarios include ETL pipelines, analytics on the lakehouse, training ML models and prototyping generative AI applications under consistent governance.

How much does Amazon SageMaker Unified Studio cost?

There is no separate charge for Unified Studio itself. You pay only for the underlying AWS resources and services you use, such as compute, storage, notebooks and SageMaker Catalog, on a pay-as-you-go basis. Core operations like domain, project and user management are available at no additional cost.

Is Amazon SageMaker Unified Studio available in the EU?

Yes. Since general availability in March 2025, Unified Studio is offered in multiple AWS regions, including five EU regions: Ireland, Frankfurt, London, Paris and Stockholm. This lets you process and store data within the EU.

AWS Cloud Expertise

innFactory is an AWS Reseller with certified cloud architects. We provide consulting, implementation, and managed services for AWS.

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