G2 Vendor Directory

MLlib vs. scikit-learn

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

MetricMLlib

by The Apache Software Foundation

scikit-learn

by scikit-learn

Overall rating4.14.8
Review count1460
Ease of use9.09.6
Ease of setup8.99.7
Quality of support7.79.4
Meets requirements8.79.6
NPS35.71428690
Small Business21.4%28.3%
Mid-Market50.0%31.7%
Enterprise28.6%40.0%
Total page views22197
Total LLM citations6381

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

    scikit-learn

    Scikit-learn is a software machine learning library for the Python programming language that has a various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

    Pros

    • Usage Frequency
    • Machine Learning
    • Ease of Use