---
title: MLlib Reviews
meta_title: 'MLlib Reviews 2026: Details, Pricing, & Features | G2'
meta_description: Filter 14 reviews by the users' company size, role or industry to
  find out how MLlib works for a business like yours.
aggregate_rating:
  rating_value: 4.1
  review_count: 14
  scale: '5'
date_modified: '2026-08-07'
parent_category:
  name: Artificial Intelligence
  url: https://www.g2.com/categories/artificial-intelligence
---


# MLlib Reviews
**Vendor:** The Apache Software Foundation  
**Category:** [Machine Learning Software](https://www.g2.com/categories/machine-learning)  
**Average Rating:** 4.1/5.0  
**Total Reviews:** 14
## About 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.




## MLlib Reviews
  ### 1. Distributed ML in Spark with limited flexibility, especially for advanced algorithms

**Rating:** 2.5/5.0 stars

**Reviewed by:** Saeid A. | Data Scientist and Researcher, Outsourcing/Offshoring, Enterprise (> 1000 emp.)

**Reviewed Date:** April 20, 2018

**What do you like best about MLlib?**

It is distributed and allow distributed execution of model training ans well as model scoring. It helps to leverage benefit of Spark without using Scala. It delivers Spark ML with Python!

High performance since it is a RDD-based data modeling package.

Fairly nice documentation.

**What do you dislike about MLlib?**

It is rigid with some of the algorithms, specially with advanced one like neural network. For instance, you are unable to change activation functions of a neural network. You can either use Sigmoid for all the layers, or tanh which is not really making sense!

Evaluation metrics are not as rich as packages like Scikit-Learn.

Not all its functionalities implemented in Python. Many are Scala-based yet.

**Recommendations to others considering MLlib:**

If you bother about advanced algorithm in specific neural network, do not use MLlib as it does give you least flexibility in customizing the network. 

Perhaps it is great for regression and decision tree in distributed environment.

**What problems is MLlib solving and how is that benefiting you?**

MLlib has both classification and regression algorithms under supervised learning and also k-means under unsupervised learning.

The beauty of the package lies in its distributed execution.



- [View MLlib pricing details and edition comparison](https://www.g2.com/products/mllib/reviews?filters%5Bnps_score%5D%5B%5D=3&section=pricing&secure%5Bexpires_at%5D=2026-08-13+13%3A59%3A50+-0500&secure%5Bsession_id%5D=732270f7-50ff-4069-b883-a7d3c63b50c6&secure%5Btoken%5D=35cfb32816db802786820dee0f84e3530e0a1fa3cfdd840c562f3996ff1b30bf&format=llm_user)

## MLlib Features
**Additional Functionality**
- Tagging
- Natural Language Processing
- Data Extraction
- Multi-Language
- Predictive Analytics
- Drag & Drop
- Speech Recognition
- Reporting/Analytics
- Data Storage Management
- Virtual Personal Assistant (VPA)
- AI Copilot
- Customer Segmentation
- Collaboration Tools
- Data Import/Export
- Generative AI
- For eCommerce
- Role-Based Permissions
- Customizable Branding
- Search/Filter
- Monitoring
- Document Management
- API
- Data Visualization
- Trend Analysis
- Machine Learning
- Access Controls/Permissions
- Alerts/Escalation
- Performance Metrics
- Real-Time Data
- Third-Party Integrations
- Mobile App
- Multiple Data Sources
- For Sales Teams/Organizations
- Sentiment Analysis
- Activity Dashboard
- Chatbot
- Workflow Automation

**Integration - Machine Learning**
- Integration
- Third-Party Integrations

**Learning - Machine Learning**
- Training Data
- Actionable Insights
- Algorithm

**Additional Functionality**
- Predictive Modeling
- Configurable Workflow
- Tagging
- Data Import/Export
- API
- Predictive Analytics
- Data Visualization
- Endpoint Management
- Multiple Data Sources
- No-Code
- Data Preparation
- Auditing
- Collaboration Tools
- Big Data Analytics
- ML Algorithm Library
- Data Management
- Activity Dashboard
- Data Capture and Transfer
- Activity Tracking
- Data Connectors
- Data Security
- Data Extraction
- Reporting & Statistics
- Workflow Management
- AI Copilot

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