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Altair RapidMiner vs Cloudera Data Science Workbench comparison

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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
11th
Average Rating
8.4
Reviews Sentiment
6.9
Number of Reviews
26
Ranking in other categories
Predictive Analytics (6th)
Cloudera Data Science Workb...
Ranking in Data Science Platforms
24th
Average Rating
7.0
Reviews Sentiment
6.9
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of September 2026, in the Data Science Platforms category, the mindshare of Altair RapidMiner is 3.1%, down from 7.4% compared to the previous year. The mindshare of Cloudera Data Science Workbench is 1.6%, up from 1.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Altair RapidMiner3.1%
Cloudera Data Science Workbench1.6%
Other95.3%
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.
Ismail Peer - PeerSpot reviewer
Program Management Lead Advisor at Unionbank Philippines
Useful for data science modeling but improvement is needed in MLOps and pricing
If you don't configure CDSW well, then it might be not useful for you. Deploying the tool can vary in complexity, but most of the time, it's relatively simple and straightforward. Triggering a job from data to production is easy, as the platform automates the deployment process. However, ensuring optimal resource allocation is essential for smooth operations.

Quotes from Members

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

Pros

"The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model."
"RapidMiner is very easy to use."
"Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations."
"One of the most valuable features is the built-in data tuning feature. Once the model is built, we often struggle to increase its accuracy, but RapidMiner allows us to fine-tune variables. For Example, when working on a project, we can adjust the number of nodes or the depth of trees to see how accuracy changes. This flexibility lets us achieve higher accuracy compared to traditional automated machine-learning models"
"It's helpful if you want to make informed decisions using data, as we can take the information, tease out the attributes, and label everything, making it suitable for profiling and forecasting in any industry."
"Using the GUI, I can have models and algorithms drag and drop nodes."
"I like not having to write all solutions from code. Being able to drag and drop controls, enables me to focus on building the best model, without needing to search for syntax errors or extra libraries."
"We value the collaboration and governance features because it's a comprehensive platform that covers everything from data extraction to modeling operations in the ML language. RapidMiner is competitive in the ML space."
"The Cloudera Data Science Workbench is customizable and easy to use."
"I appreciate CDSW's ability to logically segregate environments, such as data, DR, and production, ensuring they don't interfere with each other. The deployment of machine learning is fast and easy to manage. Its API calls are also fast."
 

Cons

"I would like to see more integration capabilities."
"I would like to see all users have access to all of the deep learning models, and that they can be used easily."
"In terms of the UI and SaaS, the user interface with KNIME is more appealing than RapidMiner."
"Many things in the interface look nice, but they aren't of much use to the operator. It already has lots of variables in there."
"RapidMiner can improve deep learning by enhancing the features."
"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."
"Regarding Altair RapidMiner's AI capabilities, I think its governance and security are not the greatest."
"RapidMiner loads very slowly, which is something that should be improved."
"The tool's MLOps is not good. It's pricing also needs to improve."
"We found this solution a little bit difficult to scale."
"Running this solution requires a minimum of 12GB to 16GB of RAM."
 

Pricing and Cost Advice

"I used an educational license for this solution, which is available free of charge."
"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."
"The client only has to pay the licensing costs. There are not any maintenance or hidden costs in addition to the license."
"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."
"The product is expensive."
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Top Industries

By visitors reading reviews
Manufacturing Company
13%
Financial Services Firm
10%
University
9%
Computer Software Company
8%
Financial Services Firm
27%
Outsourcing Company
12%
Construction Company
6%
Healthcare Company
6%
 

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...
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Also Known As

No data available
CDSW
 

Overview

 

Sample Customers

PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen
IQVIA, Rush University Medical Center, Western Union
Find out what your peers are saying about Altair RapidMiner vs. Cloudera Data Science Workbench and other solutions. Updated: September 2026.
913,806 professionals have used our research since 2012.