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What is ER/Studio Enterprise Edition?
ER/Studio is an enterprise data modeling and architecture platform that helps organizations design, align, and govern data across complex, distributed environments. It translates business requirements into technical implementation through integrated conceptual, logical, and physical models, creating a consistent foundation for analytics, AI initiatives, modernization, compliance, and operational systems. ER/Studio supports modern data architectures, including data warehouses, lakehouses, data mesh frameworks, and data vault methodologies, ensuring models reflect how platforms are built today. By maintaining clear relationships between definitions and database structures, it establishes a trusted, enterprise-wide view of data.
Collaboration is enabled through a centralized, multi-user repository with version control, role-based access, and parallel development. Teams can work simultaneously while preserving model integrity and full change history. The web-based portal, Team Server, extends visibility beyond architects, allowing business and technical stakeholders to explore models, review metadata, and provide feedback through a browser interface. This shared environment improves transparency and alignment between design and execution.
Governance and standardization are embedded within the modeling process. Business glossaries and data dictionaries link directly to technical objects so approved definitions remain synchronized with implementations. Built-in impact analysis provides visibility into downstream dependencies before changes are deployed, reducing risk and strengthening coordination. Metadata can be synchronized with platforms such as Microsoft Purview and Collibra to enhance lineage visibility, documentation accuracy, and compliance oversight.
Available in Standard, Professional, and Enterprise editions, ER/Studio scales from individual practitioners to enterprise-wide architecture programs with advanced collaboration and governance needs.
What is Amazon SageMaker?
Amazon SageMaker is a robust platform designed to help developers efficiently build, train, and deploy machine learning models. It unites a wide range of tools in a single, integrated environment that accelerates the creation and deployment of both traditional machine learning models and generative AI applications. SageMaker enables seamless data access from diverse sources like Amazon S3 data lakes, Redshift data warehouses, and third-party databases, while offering secure, real-time data processing. The platform provides specialized features for AI use cases, including generative AI, and tools for model training, fine-tuning, and deployment at scale. It also supports enterprise-level security with fine-grained access controls, ensuring compliance and transparency throughout the AI lifecycle. By offering a unified studio for collaboration, SageMaker improves teamwork and productivity. Its comprehensive approach to governance, data management, and model monitoring gives users full confidence in their AI projects.
Integrations Supported
Amazon Redshift
AWS AI Factories
AWS Deep Learning Containers
AWS IoT
Amazon EC2 Inf1 Instances
Amazon EC2 P5 Instances
BentoML
Databricks
Determined AI
JFrog ML
Integrations Supported
Amazon Redshift
AWS AI Factories
AWS Deep Learning Containers
AWS IoT
Amazon EC2 Inf1 Instances
Amazon EC2 P5 Instances
BentoML
Databricks
Determined AI
JFrog ML
API Availability
Has API
API Availability
Has API
Pricing Information
$2,687 per user
Subscription-based pricing.
Standard: $2,687 per user
Professional: $3,693 per user
Enterprise: Custom
Standard: $2,687 per user
Professional: $3,693 per user
Enterprise: Custom
Free Version
Free Trial Offered?
Pricing Information
Try free for two months
Free Version
Free Trial Offered?
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
ER/Studio
Date Founded
2004
Company Location
United States
Company Website
erstudio.com
Company Facts
Organization Name
Amazon
Date Founded
1994
Company Location
United States
Company Website
aws.amazon.com/sagemaker/
Categories and Features
Data Governance
Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management
Enterprise Architecture
Application Portfolio Management
Architecture Governance
Capability Mapping
Diagramming
Idea Management
Modeling & Simulation
Project Management
Risk Assessment
Transformation Roadmapping
Version Control
Categories and Features
Artificial Intelligence
Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)
Data Governance
Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management
Data Labeling
Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
