Altair RapidMiner vs Cloudera Data Science Workbench comparison

Altair and Cloudera are both solutions in the Data Science Platforms category. Altair is ranked #7 with an average rating of 8.1, while Cloudera is ranked #23 with an average rating of 6.0. Altair holds a 7.0% mindshare in Data Science Platforms, compared to Cloudera’s 1.3% mindshare. Additionally, 96% of Altair users are willing to recommend the solution, compared to 66% of Cloudera users who would recommend it.

Altair RapidMiner

Read 24 Altair RapidMiner reviews

4,556 Views
3,964 Comparison Views

96% willing to recommend

Cloudera Data Science Workb...

Read 2 Cloudera Data Science Workbench reviews

782 Views
766 Comparison Views

66% willing to recommend

Altair RapidMiner

Cloudera Data Science Workb...

Comparison Buyer's Guide

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Executive SummaryUpdated on Sep 14, 2025

Altair RapidMiner and Cloudera Data Science Workbench are competitive in data science and machine learning. Altair RapidMiner has an edge with pricing and support, appealing to cost-sensitive users, while Cloudera Data Science Workbench offers superior features for comprehensive data tasks.

Features: Altair RapidMiner features intuitive workflows, automated data preparation, and user-centric design, ideal for quick analysis. Cloudera Data Science Workbench offers collaborative environments, seamless integration with big data tools, and a focus on scalability.

Ease of Deployment and Customer Service: Altair RapidMiner offers a straightforward deployment and supportive customer service for organizations seeking simplicity. Cloudera Data Science Workbench, while involving a more complex deployment, provides comprehensive documentation and support.

Pricing and ROI: Altair RapidMiner presents low upfront costs with good ROI for small to medium businesses. Cloudera Data Science Workbench, with higher setup fees, offers significant ROI for enterprises leveraging its features for large-scale projects.

To learn more, read our detailed Altair RapidMiner vs. Cloudera Data Science Workbench Report (Updated: September 2025).

Buyer's Guide

Altair RapidMiner vs. Cloudera Data Science Workbench

September 2025

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Helped 872,706 peers since 2012

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

7th

Average Rating

8.6

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Predictive Analytics (3rd)

Cloudera Data Science Workb...

Ranking in Data Science Platforms

23rd

Average Rating

7.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of October 2025, in the Data Science Platforms category, the mindshare of Altair RapidMiner is 7.0%, down from 7.5% compared to the previous year. The mindshare of Cloudera Data Science Workbench is 1.3%, down from 1.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
Altair RapidMiner	7.0%
Cloudera Data Science Workbench	1.3%
Other	91.7%

Data Science Platforms

Featured Reviews

Rathnam Makam

Senior Technical Manager at a computer software company with 1,001-5,000 employees

A no-code tool that helps to build machine learning models

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. I haven't explored the tool's latest version, so I'm unaware of the current features. However, I think it would be beneficial if they could enhance capabilities related to deep neural networks, provide better support for generating UI, and allow for importing and utilizing large language models.

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Ismail Peer

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.

Read full review

Quotes from Members

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

Pros

"It's helpful if you want to make informed decisions using data. We can take the information, tease out the attributes, and label everything. It's suitable for profiling and forecasting in any industry."

"RapidMiner is very easy to use."

"The solution is stable."

"The most valuable feature of RapidMiner is that it is code free. It is similar to playing with Lego pieces and executing after you are finished to see the results. Additionally, it is easy to use and has interesting utilities when preparing the data. It has a utility to automatically launch a series of models and show the comparisons. When finished with the comparisons you can select the best one, and deploy it automatically."

"What I like about RapidMiner is its all-in-one nature, which allows me to prepare, extract, transform, and load data within the same tool."

"Altair RapidMiner is easy to use and intuitive with no coding required, making it a low code tool."

"Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations."

"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."

More Altair RapidMiner pros

"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

"RapidMiner isn't cheap. It's a complete solution, but it's costly."

"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."

"Altair RapidMiner needs updates to its examples, particularly in business and marketing areas, and to the tool itself. The user interface should be improved."

"A great product but confusing in some way with regard to the user interface and integration with other tools."

"The server product has been getting updated and continues to be better each release. When I started using RapidMiner, it was solid but not easy to set up and upgrade."

"It would be helpful to have some tutorials on communicating with Python."

"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 would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models."

More Altair RapidMiner cons

"The tool's MLOps is not good. It's pricing also needs to improve."

"Running this solution requires a minimum of 12GB to 16GB of RAM."

Pricing and Cost Advice

"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."

"For the university, the cost of the solution is free for the students and teachers."

"I used an educational license for this solution, which is available free of charge."

"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

University

11%

Computer Software Company

11%

Manufacturing Company

10%

Educational Organization

Financial Services Firm

35%

Computer Software Company

Healthcare Company

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	12
Midsize Enterprise	5
Large Enterprise	8

No data available

Questions from the Community

What do you like most about RapidMiner?

RapidMiner is a no-code machine learning tool. I can install it on my local machine and work with smaller datasets. It can also connect to databases, allowing me to build models directly on the dat...

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What is your experience regarding pricing and costs for RapidMiner?

I started with a trial version. We are likely to purchase a license, which may offer additional features.

See all answers

What needs improvement with RapidMiner?

Currently, I am unsure of all the AI features available in Altair RapidMiner, particularly advanced AI capabilities like neural networks and deep learning. It would be beneficial if the platform co...

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What do you like most about Cloudera Data Science Workbench?

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...

See all answers

What needs improvement with Cloudera Data Science Workbench?

The tool's MLOps is not good. It's pricing also needs to improve.

See all answers

What is your primary use case for Cloudera Data Science Workbench?

We have different use cases. Our banking use case uses machine learning to identify customer life events and recommend the best-suited card products. These machine-learning models are deployed in o...

See all answers

Comparisons

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Compared 47% of the time

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Compared 14% of the time

Tableau Enterprise vs Altair RapidMiner

Compared 8% of the time

Alteryx vs Altair RapidMiner

Compared 6% of the time

Microsoft Azure Machine Learning Studio vs Altair RapidMiner

Compared 4% of the time

More Altair RapidMiner Competitors

Databricks vs Cloudera Data Science Workbench

Compared 33% of the time

Amazon SageMaker vs Cloudera Data Science Workbench

Compared 20% of the time

Dataiku vs Cloudera Data Science Workbench

Compared 19% of the time

KNIME Business Hub vs Cloudera Data Science Workbench

Compared 12% of the time

Microsoft Azure Machine Learning Studio vs Cloudera Data Science Workbench

Compared 9% of the time

More Cloudera Data Science Workbench Competitors

Product Reports

Buyer's Guide

Altair RapidMiner

October 2025

Download Altair RapidMiner product report

Buyer's Guide

Data Science Platforms

October 2025

Download Cloudera Data Science Workbench product report

Also Known As

No data available

CDSW

Overview

Altair RapidMiner is a leading platform for data science and machine learning, offering a user-friendly interface with powerful tools for predictive analytics. It supports integration with APIs, Python, and cloud services for streamlined workflow creation.

RapidMiner provides an efficient data science environment featuring drag-and-drop functionality, automation tools, and a wide array of algorithms, making it adaptable for novices and experts alike. Users benefit from easy data preparation and analysis alongside robust support from a vibrant community. Challenges include better onboarding and deep learning model accessibility, alongside calls for enhanced image processing and large language model integration.

What features make Altair RapidMiner stand out?

Data science tools: Facilitates machine learning and predictive analytics.
Code-optional GUI: Enables non-programmers to create workflows seamlessly.
Integration: Supports APIs, Python, and cloud services.
Drag-and-drop functionality: Simplifies workflow creation for users.
Algorithm variety: Offers diverse methods for data analysis.

What benefits and ROI should users consider when evaluating?

Efficiency: Saves time in data preparation and workflow automation.
Accessibility: Intuitive design aids beginners and experts.
Community: Access to extensions and collaborative resources.
Documentation: Comprehensive tutorials enhance learning.

Altair RapidMiner is extensively used in business and academia, facilitating tasks like predictive analytics, segmentation, and deployment. In education, it supports data science teaching and research, while in industries such as telecom, banking, and healthcare, it's used for data mining, decision trees, and market analysis.

Altair

Cloudera Data Science Workbench (CDSW) makes secure, collaborative data science at scale a reality for the enterprise and accelerates the delivery of new data products. With CDSW, organizations can research and experiment faster, deploy models easily and with confidence, as well as rely on the wider Cloudera platform to reduce the risks and costs of data science projects. Access any data anywhere – from cloud object storage to data warehouses, CDSW provides connectivity not only to CDH but the systems your data science teams rely on for analysis.

Cloudera

Sample Customers

PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen

IQVIA, Rush University Medical Center, Western Union

Buyer's Guide

Altair RapidMiner vs. Cloudera Data Science Workbench

September 2025

Free Report: Altair RapidMiner vs. Cloudera Data Science Workbench

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