Amazon SageMaker vs. SAS Model Manager
A side-by-side comparison based on G2 review data.
| Metric | Amazon SageMaker | SAS Model Manager |
|---|---|---|
| Overall rating | 4.3 | 4.6 |
| Review count | 57 | 70 |
| Ease of use | 8.6 | 8.3 |
| Ease of setup | 8.6 | 7.0 |
| Quality of support | 8.9 | 8.9 |
| Meets requirements | 8.9 | 8.6 |
| NPS | 46.296296 | 78.571429 |
| Small Business | 30.9% | 27.1% |
| Mid-Market | 34.5% | 15.7% |
| Enterprise | 34.5% | 57.1% |
| Total page views | 401 | 91 |
| Total LLM citations | 1,606 | 220 |
Amazon SageMaker
Amazon SageMaker is a fully managed service that enables data scientists and developers to build, train, and deploy machine learning (ML) models at scale. It provides a comprehensive suite of tools and infrastructure, streamlining the entire ML workflow from data preparation to model deployment. With SageMaker, users can quickly connect to training data, select and optimize algorithms, and deploy models in a secure and scalable environment.
- Ease of Use
- Implementation Ease
- Model Management
- Time-Saving
- Features
- Fast Processing
SAS Model Manager
SAS® Model Manager is a web-based application that enables organizations to register, modify, track, score, publish, and report on analytical models. Organizations can store models within folders or projects, develop and validate candidate models, and assess candidate models for champion model selection. They can then publish and monitor champion models. All model development and model maintenance personnel, including data modelers, validation testers, scoring officers, and analysts can use SAS Model Manager.
- Model Variety
- Model Management
- Analytics
- Problem Solving
- Machine Learning
- Time-Saving