MLlib vs. SAS Model Manager
A side-by-side comparison based on G2 review data.
| Metric | MLlib | SAS Model Manager |
|---|---|---|
| Overall rating | 4.1 | 4.6 |
| Review count | 14 | 70 |
| Ease of use | 9.0 | 8.3 |
| Ease of setup | 8.9 | 7.0 |
| Quality of support | 7.7 | 8.9 |
| Meets requirements | 8.7 | 8.6 |
| NPS | 35.714286 | 78.571429 |
| Small Business | 21.4% | 27.1% |
| Mid-Market | 50.0% | 15.7% |
| Enterprise | 28.6% | 57.1% |
| Total page views | 22 | 91 |
| Total LLM citations | 6 | 220 |
MLlib
MLlib is Spark's machine learning (ML) library that make practical machine learning scalable and easy it provides ML Algorithms: common learning algorithms such as classification, regression, clustering, and collaborative filtering, feature extraction, transformation, dimensionality reduction, and selection, tools for constructing, evaluating, and tuning ML Pipelines, saving and load algorithms, models, and Pipelines and linear algebra, statistics, data handling, etc.
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