Altair RapidMiner vs Cloudera Data Science Workbench comparison

Altair and Cloudera are both solutions in the Data Science Platforms category. Altair is ranked #6 with an average rating of 8.3, while Cloudera is ranked #22 with an average rating of 6.0. Altair holds a 7.8% mindshare in Data Science Platforms, compared to Cloudera’s 1.3% mindshare. Additionally, 95% of Altair users are willing to recommend the solution, compared to 66% of Cloudera users who would recommend it.

Altair RapidMiner

Read 23 Altair RapidMiner reviews

5,232 Views
4,119 Comparison Views

95% willing to recommend

Cloudera Data Science Workb...

Read 2 Cloudera Data Science Workbench reviews

1,076 Views
919 Comparison Views

66% willing to recommend

Altair RapidMiner

Cloudera Data Science Workb...

Comparison Buyer's Guide

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Executive SummaryUpdated on Mar 4, 2025

Altair RapidMiner and Cloudera Data Science Workbench are products in the data analytics and machine learning space. Cloudera Data Science Workbench seems to have the upper hand due to its superior functionality.

Features: Altair RapidMiner is recognized for predictive analytics, automated modeling, and user-centric design. Cloudera Data Science Workbench is known for robust integration, scalability suited to large enterprises, and extensive functionality.

Ease of Deployment and Customer Service: Altair RapidMiner offers a straightforward deployment process and proactive customer service. Cloudera Data Science Workbench, while complex to deploy, benefits from comprehensive support and documentation, requiring more technical expertise initially.

Pricing and ROI: Altair RapidMiner offers competitive pricing, providing quicker ROI for smaller and mid-sized businesses. Cloudera Data Science Workbench, with a higher initial cost, delivers better ROI for organizations scaling sophisticated data operations.

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

Buyer's Guide

Altair RapidMiner vs. Cloudera Data Science Workbench

March 2025

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Helped 842,592 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

6th

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

22nd

Average Rating

7.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of March 2025, in the Data Science Platforms category, the mindshare of Altair RapidMiner is 7.8%, up from 6.5% compared to the previous year. The mindshare of Cloudera Data Science Workbench is 1.3%, down from 1.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

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.

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Quotes from Members

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

Pros

"The most valuable feature of RapidMiner is that it can read a large number of file formats including CSV, Excel, and in particular, SPSS."

"The most valuable feature is what the product sets out to do, which is extracting information and data."

"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 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."

"RapidMiner for Windows is an excellent graphical tool for data science."

"The best part of RapidMiner is efficiency."

"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"

More Altair RapidMiner pros

"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."

"The Cloudera Data Science Workbench is customizable and easy to use."

Cons

"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."

"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."

"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."

"I would like to see all users have access to all of the deep learning models, and that they can be used easily."

"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."

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

"Improve the online data services."

"The product must provide data-cleaning features."

More Altair RapidMiner cons

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

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

Pricing and Cost Advice

"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."

"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 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."

"The product is expensive."

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Top Industries

By visitors reading reviews

University

11%

Computer Software Company

11%

Financial Services Firm

10%

Educational Organization

10%

Financial Services Firm

34%

Manufacturing Company

10%

Healthcare Company

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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'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.

See all answers

What needs improvement with RapidMiner?

The product must provide data-cleaning features. I could not use RapidMiner for data cleaning in one of my projects and had to use Python instead.

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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 16% of the time

Alteryx vs Altair RapidMiner

Compared 8% of the time

Tableau vs Altair RapidMiner

Compared 7% of the time

Microsoft Azure Machine Learning Studio vs Altair RapidMiner

Compared 3% of the time

More Altair RapidMiner Competitors

Amazon SageMaker vs Cloudera Data Science Workbench

Compared 31% of the time

Databricks vs Cloudera Data Science Workbench

Compared 28% of the time

Dataiku vs Cloudera Data Science Workbench

Compared 15% of the time

Google Cloud Datalab vs Cloudera Data Science Workbench

Compared 9% of the time

KNIME vs Cloudera Data Science Workbench

Compared 9% of the time

More Cloudera Data Science Workbench Competitors

Product Reports

Buyer's Guide

Altair RapidMiner

February 2025

Download Altair RapidMiner product report

Buyer's Guide

Data Science Platforms

February 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

March 2025

Free Report: Altair RapidMiner vs. Cloudera Data Science Workbench

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