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Altair RapidMiner vs Domino Data Science Platform comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jun 3, 2026

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Altair RapidMiner
Ranking in Data Science Platforms
10th
Average Rating
8.4
Reviews Sentiment
6.9
Number of Reviews
26
Ranking in other categories
Predictive Analytics (5th)
Domino Data Science Platform
Ranking in Data Science Platforms
19th
Average Rating
7.6
Reviews Sentiment
6.7
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of June 2026, in the Data Science Platforms category, the mindshare of Altair RapidMiner is 3.4%, down from 7.8% compared to the previous year. The mindshare of Domino Data Science Platform is 2.0%, down from 2.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Altair RapidMiner3.4%
Domino Data Science Platform2.0%
Other94.6%
Data Science Platforms
 

Featured Reviews

SP
Solution Architect at Hitachi Digital Services
Visual workflows have empowered teams to build and deploy reliable predictive maintenance models
The best features Altair RapidMiner offers in my experience are the visual workflow designer in AI Studio, which is the foundation of everything. Building complete machine learning pipelines, data ingestion, transformation, feature engineering, model training, validation, and deployment in a drag-and-drop visual environment without extensive coding is what makes this accessible to organizations that cannot staff a team of Python developers for every analytics project. That capability opens the door.Auto Model is the feature I lean on most when doing rapid prototyping with clients. It evaluates multiple algorithms automatically, surfaces the best-performing model for the data, and explains why. That dramatically compresses the experimentation phase. What would take a data scientist days of manual testing, Auto Model does in an hour.
AS
Machine Learning Engineer at Unemployed
Accelerated machine learning model development with seamless deployment
We used Domino Data Science Platform for developing and working with machine learning models. It facilitated end-to-end development processes. Domino is based on Git, enabling collaboration similar to using Git. Each user operates on their own equivalent of a branch or fork, and once finished, they…

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"RapidMiner for Windows is an excellent graphical tool for data science."
"Using the GUI, I can have models and algorithms drag and drop nodes."
"The most valuable features are the Binary classification and Auto Model."
"The tools have a complete function for doing data."
"I've been using a lot of components from the Strategic Extension and Python Extension."
"It is easy to use and has a huge community that I can rely on for help. Moreover, it is interactive."
"Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations."
"The best thing about RapidMiner is efficiency."
"We primarily use the solution for customer retention, but there are a lot of use cases for this particular product."
"The scalability of the solution is good; I'd rate it four out of five."
"The workspaces, which are like wrappers of Docker containers, made it easy to start development environments using Domino."
 

Cons

"RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models."
"The biggest problem, not from a platform process, but from an avoidance process, is when you work in a heavily regulated BFSI environment, like banking and finance."
"RapidMiner isn't cheap. It's a complete solution, but it's costly."
"If they could include video tutorials, people would find that quite helpful."
"I think it's a great product but confusing in some way with regard to the user interface and integration with other tools."
"RapidMiner is not utterly intuitive for beginners."
"One challenge I encountered while implementing RapidMiner was the lack of documentation. Since there aren't as many users, finding resources to learn the tool was initially difficult. To overcome this hurdle, I believe RapidMiner could improve by providing more tutorials tailored for new users."
"The visual interface could use something like the-drag-and-drop features which other products already support. Some additional features can make RapidMiner a better tool and maybe more competitive."
"The deployment of large language models (LLMs) could be improved."
"The predictive analysis feature needs improvement."
 

Pricing and Cost Advice

"For the university, the cost of the solution is free for the students and teachers."
"Although we don't pay licensing fees because it is being used within the university, my understanding is that the cost is between $5,000 and $10,000 USD per year."
"I'm not fully aware of RapidMiner's price because we had licenses provided, but from my analysis, it's moderately priced, not too high or too low. It's worth the investment."
"I used an educational license for this solution, which is available free of charge."
"The client only has to pay the licensing costs. There are not any maintenance or hidden costs in addition to the license."
Information not available
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Top Industries

By visitors reading reviews
Manufacturing Company
12%
Financial Services Firm
11%
University
9%
Computer Software Company
8%
Financial Services Firm
36%
Manufacturing Company
8%
Insurance Company
8%
Healthcare Company
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business12
Midsize Enterprise5
Large Enterprise10
No data available
 

Questions from the Community

What is your experience regarding pricing and costs for RapidMiner?
My experience with pricing, setup cost, and licensing shows that the licensing model is based on Altair Units, which is their shared token-based system across their product portfolio and is flexibl...
What needs improvement with RapidMiner?
Altair RapidMiner can be improved by enhancing the newer GenAI features, which are interesting but honestly still quite early, and the documentation does not yet match the ambition of what they are...
What is your primary use case for RapidMiner?
My main use case for Altair RapidMiner is predictive quality analysis on the manufacturing site, as Wagner Spraytech manufactures spray finishing equipment and we generate a significant amount of o...
What needs improvement with Domino Data Science Platform?
The deployment of large language models (LLMs) could be improved. Currently, Domino provides a simple server that cannot handle big deployments, which is not suitable for LLMs.
What is your primary use case for Domino Data Science Platform?
We used Domino Data Science Platform for developing and working with machine learning models. It facilitated end-to-end development processes. Domino is based on Git, enabling collaboration similar...
What advice do you have for others considering Domino Data Science Platform?
It's important to have a DevOps team well-versed with cloud-native solutions to manage Domino effectively. Relying solely on data scientists might not be sufficient. I'd rate the solution eight out...
 

Also Known As

No data available
Domino Data Lab Platform
 

Interactive Demo

Demo not available
 

Overview

 

Sample Customers

PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen
Allstate, GSK, AstraZeneca, Federal Reserve, US Navy, Bristol Myers Squibb, Bayer, BNP Paribas, Moodys, New York Life
Find out what your peers are saying about Altair RapidMiner vs. Domino Data Science Platform and other solutions. Updated: June 2026.
900,747 professionals have used our research since 2012.