G2 Vendor Directory

MLlib vs. SAS Model Manager

A side-by-side comparison based on G2 review data.

MetricMLlib

by The Apache Software Foundation

SAS Model Manager

by SAS Institute

Overall rating4.14.6
Review count1470
Ease of use9.08.3
Ease of setup8.97.0
Quality of support7.78.9
Meets requirements8.78.6
NPS35.71428678.571429
Small Business21.4%27.1%
Mid-Market50.0%15.7%
Enterprise28.6%57.1%
Total page views2291
Total LLM citations6220

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.

Pros

    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.

    Pros

    • Model Variety
    • Model Management
    • Analytics
    • Problem Solving
    • Machine Learning
    • Time-Saving