---
title: Apache SystemML Reviews
meta_title: 'Apache SystemML Reviews 2026: Details, Pricing, & Features | G2'
meta_description: Filter reviews by the users' company size, role or industry to find
  out how Apache SystemML works for a business like yours.
aggregate_rating:
  rating_value: 4.4
  review_count: 5
  scale: '5'
date_modified: '2026-06-14'
parent_category:
  name: Artificial Intelligence
  url: https://www.g2.com/categories/artificial-intelligence
---


# Apache SystemML Reviews
**Vendor:** The Apache Software Foundation  
**Category:** [Machine Learning Software](https://www.g2.com/categories/machine-learning)  
**Average Rating:** 4.4/5.0  
**Total Reviews:** 5
## About Apache SystemML
Apache SystemML is a machine learning platform optimal for big data that provides an optimal workplace for machine learning using big data, it can be run on top of Apache Spark, where it automatically scales your data, line by line, determining whether your code should be run on the driver or an Apache Spark cluster.




## Apache SystemML Reviews
  ### 1. Apache SystemML is Good to work with Machine Learning along with Bigdata

**Rating:** 4.0/5.0 stars

**Reviewed by:** RAKESH K. | Assistant Professor and Junior Research Fellow, Education Management, Mid-Market (51-1000 emp.)

**Reviewed Date:** March 05, 2024

**What do you like best about Apache SystemML?**

Apache SystemML is from IBM which declared it as open source. Apache SystemML is good platform to solve Machine Learning problems. In Machine Learning we need of a lot of data and handling those bigdata is not an easy task which can be done seamlessly with Apache SystemML. It is also helpful for data scientist or engineers. It customizes and optimizes algorithms based on there characteristics. It supports popular R, Python language which is helpful also. With the add on help of apache spark it flourish it's accuracy well. Apache SystemML automatically generate hybrid runtime plans ranging from single node, in memory computation, distributed computation on Apache Hadoop and Spark.

**What do you dislike about Apache SystemML?**

Apache SystemML is still struggling for customer acquisition. Also it lacks of project collaboration. Sometimes it seems slow while processing data. Though there is documentations but it needs an update periodically.

**What problems is Apache SystemML solving and how is that benefiting you?**

We do work in the field of Machine Learning with this tool which helps us to optimize using optimizers functions. Using Apache SystemML we create and extend Machine Learning frameworks which are commercial friendly and scalable. We use DML, optimizer stack and LDescribe for efficiently use ML algorithms.

  ### 2. My feedback on Apache SystemML

**Rating:** 4.0/5.0 stars

**Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.)

**Reviewed Date:** June 06, 2018

**What do you like best about Apache SystemML?**

Ease of use , integration with other downstream process 

**What do you dislike about Apache SystemML?**

Not enough documentation , network latency

**What problems is Apache SystemML solving and how is that benefiting you?**

seamless integration with platform as a service offering 


## Apache SystemML Discussions
  - [What is Apache SystemML used for?](https://www.g2.com/discussions/apache-systemml-what-is-apache-systemml-used-for)
  - [What is Apache SystemML used for?](https://www.g2.com/discussions/what-is-apache-systemml-used-for)

- [View Apache SystemML pricing details and edition comparison](https://www.g2.com/products/apache-systemml/reviews?filters%5Bnps_score%5D%5B%5D=4&section=pricing&secure%5Bexpires_at%5D=2026-08-07+13%3A54%3A46+-0500&secure%5Bsession_id%5D=875f7309-39d3-4346-908a-f11c38f288a9&secure%5Btoken%5D=4a57a16b2c18691bf8426845035d87b68e6c78ef6f923441ce43dbc9d4bd070e&format=llm_user)

## Apache SystemML 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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