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Altair RapidMiner Reviews

Vendor: Altair
4.3 out of 5
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What is Altair RapidMiner?

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.

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Altair RapidMiner is the #2 ranked solution in top Predictive Analytics solutions and #7 ranked solution in top Data Science Platforms. PeerSpot users give Altair RapidMiner an average rating of 8.6 out of 10. Altair RapidMiner is most commonly compared to Databricks: Altair RapidMiner vs Databricks. Altair RapidMiner is popular among the large enterprise segment, accounting for 59% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a computer software company, accounting for 11% of all views.
Buyer's Guide
Altair RapidMiner
September 2025
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Altair RapidMiner mindshare

Product category:
Predictive Analytics
As of September 2025, the mindshare of Altair RapidMiner in the Predictive Analytics category stands at 11.5%, down from 18.3% compared to the previous year, according to calculations based on PeerSpot user engagement data.
Predictive Analytics Market Share Distribution
ProductMarket Share (%)
Altair RapidMiner11.5%
Alteryx15.0%
Anaplan13.8%
Other59.7%
Predictive Analytics

PeerResearch reports based on Altair RapidMiner reviews

TypeTitleDate
CategoryPredictive AnalyticsSep 13, 2025Download
ProductReviews, tips, and advice from real usersSep 13, 2025Download
ComparisonAltair RapidMiner vs AlteryxSep 13, 2025Download
ComparisonAltair RapidMiner vs SAP Analytics CloudSep 13, 2025Download
ComparisonAltair RapidMiner vs AnaplanSep 13, 2025Download
Suggested products
TitleRatingMindshareRecommending
Databricks4.1N/A96%91 interviewsAdd to research
KNIME Business Hub4.1N/A94%60 interviewsAdd to research
 
 
Key learnings from peers

Valuable Features

Altair RapidMiner boasts cutting-edge data science tools, an easy-to-use code-optional GUI, and open-source flexibility. It allows seamless integration with various programming languages and cloud platforms. Users value its efficiency, automation, and capability to handle complex datasets, offering intuitive analytics and model-building processes. With excellent documentation and community support, its Auto ML feature empowers non-coders, providing extensive capabilities in machine learning and predictive analytics. Highly appreciated are its versatility, ease of use, and quick prototyping features.
  • "Altair RapidMiner is easy to use and intuitive with no coding required, making it a low code tool."
  • "Altair RapidMiner is appreciated for its ease of use and the CRISP data mining model it supports, covering steps like data preparation, data understanding, and business understanding."
  • "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"

Room for Improvement

Altair RapidMiner requires enhancements in its user interface and integration capabilities, as well as improvements in deep learning and machine learning algorithms. Speed loading times, pricing, and ease of use for beginners need attention. Users seek wider community adoption, better online data services, and improved tutorials for Python integration. Enhanced automation, customization options, data cleaning features, and image processing capabilities are also desired. More business-oriented examples and advanced AI model suggestions are requested.
  • "Currently, I am unsure of all the AI features available in Altair RapidMiner, particularly advanced AI capabilities like neural networks and deep learning."
  • "Altair RapidMiner needs updates to its examples, particularly in business and marketing areas, and to the tool itself. The user interface should be improved."
  • "About twenty-five percent of my problems involve image processing, and I found RapidMiner lacking in this domain. While we work on OCR and similar tasks, RapidMiner hasn't been as engaged in that field as other models. Some other models also support email processing, but RapidMiner doesn't offer this feature."

Pricing

Enterprise users can experience a range of Altair RapidMiner pricing models, including a freemium option for datasets under 10,000 rows and free academic licenses. Companies find the paid licenses more affordable than competitors like SAS or SPSS, typically ranging from $5,000 to $10,000 USD per year. Multiple reviews indicate that while the solution is powerful and often costly, many consider it a valuable investment with transparent pricing and no hidden costs.
  • "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."
  • "The client only has to pay the licensing costs. There are not any maintenance or hidden costs in addition to the license."

Popular Use Cases

Altair RapidMiner is primarily used for developing and deploying machine learning workflows in business analytics, education, and data science projects. It aids in predictive analytics, data preparation, segmentation, and statistical education. Organizations apply it for customer churn prediction, financial crime management, pharmaceutical industry analysis, and psychiatric case studies. It supports teaching, data modeling, forecasting, sales analytics, and market-based analysis, proving beneficial in various industries from telecom to education.

Service and Support

Customers express positive experiences with Altair RapidMiner's customer service. Many resolve issues via community forums and resources. Technical support is rated highly, often deemed fantastic or incredible, with partners highlighting exceptional assistance. Community forums and blogs are valuable resources for resolving technical challenges, offering quick responses. Users find the software intuitive, needing minimal direct support. Even without contacting support directly, users benefit from accessible guidance through built-in features and a robust online user community.

Deployment

Altair RapidMiner's initial setup is often described as straightforward and easy to manage. Desktop versions are particularly user-friendly, requiring no additional installation. However, success with more complex deployment models demands data science knowledge. Some users found the process quick, citing instances where setup took only minutes. Users with large datasets sometimes experienced extended setup times. Effective maintenance involves a small team, and technical support from partners is often available when needed.

Scalability

User experiences with Altair RapidMiner indicate it is scalable, especially effective in sizable deployments and capable of handling large transaction volumes. It supports various deployment models, though transition to operational scenarios can be complex. Users appreciate its support for multiple data-driven tasks, but some have yet to assess its scalability, particularly with the server version. Scalability considerations include concurrent user handling and model deployment requirements. Suitable for extensive data-driven projects by data scientists and analysts.

Stability

Users generally find Altair RapidMiner stable, with no issues regarding downtime or crashes. Some mention longer loading times due to the number of models but report smooth operation after startup. A few have experienced occasional problems with extensions and primary processing tasks, particularly with the operator's toolbox, but these are not widespread. Stability is rated highly, and users appreciate its reliable performance in machine learning applications, though its performance with large datasets remains mostly untested.
These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.
Download our Altair RapidMiner Buyer's Guide for additional reliable information.

Review data by company size

By reviewers
Company SizeCount
Small Business10
Midsize Enterprise4
Large Enterprise8
By reviewers
By visitors reading reviews
Company SizeCount
Small Business222
Midsize Enterprise114
Large Enterprise487
By visitors reading reviews

Top industries

By visitors reading reviews
University
11%
Computer Software Company
11%
Manufacturing Company
10%
Educational Organization
10%
Financial Services Firm
7%
Comms Service Provider
4%
Government
4%
Healthcare Company
4%
Construction Company
3%
Retailer
3%
Legal Firm
3%
Hospitality Company
3%
Insurance Company
2%
Performing Arts
2%
Non Profit
2%
Energy/Utilities Company
2%
Real Estate/Law Firm
2%
Transportation Company
2%
Media Company
2%
Consumer Goods Company
1%
Wholesaler/Distributor
1%
Mining And Metals Company
1%
Pharma/Biotech Company
1%
Outsourcing Company
1%
Recreational Facilities/Services Company
1%
Marketing Services Firm
1%

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Learn more about Altair RapidMiner

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 RapidMiner customers

PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen

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Product Categories

Product Categories
Predictive Analytics
Data Science Platforms

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Altair RapidMiner Reviews Summary
Author infoRatingReview Summary
Professor at Instituto Superior de Contabilidade e Administraçao de Coimbra4.0I use Altair RapidMiner in my teaching and research at Coimbra Business School, finding it user-friendly with strong support for the CRISP data mining model. However, it needs better generative AI integration and more business-focused examples.
Senior Manager, Digitalization of Supply Chain& Traceability at a non-profit with 501-1,000 employees4.0I use Altair RapidMiner to analyze stock data, appreciating its intuitive, low-code interface for data preparation and initial insights. While it's stable and easy to install, I seek more advanced AI features like neural networks.
Senior Technical Manager at a computer software company with 1,001-5,000 employees4.0I use RapidMiner for educational projects and building machine learning models like clustering and decision trees. It's a user-friendly, no-code tool with many operators, though it needs better documentation and support for advanced features like deep neural networks.
Technical Support Team Lead at HCLTech4.5I used RapidMiner primarily for predicting outcomes and classifying variables in numerical datasets. Its valuable data tuning feature enhances model accuracy. However, it lacks capabilities in image and email processing. Among various solutions, RapidMiner excelled in my data tuning needs.
Student at IEBS SCHOOL4.0I used RapidMiner to analyze furniture sales and found it valuable for its all-in-one data handling capabilities and seamless integrations. However, improvements in automation and customization are needed. Despite lacking advanced features, it excels in ease of installation and affordability.
Fondateur- Data Scientist - Analyste certifié sur RapidMiner at LDK 3604.5As an electrical engineer transitioning careers, I found RapidMiner intuitive and beginner-friendly, aided by ample online resources. However, it lacks data-cleaning features, necessitating Python for such tasks in certain projects. Overall, it's powerful for sales analytics.
Student at a university with 1,001-5,000 employees4.5I use RapidMiner for my coursework, primarily for handling recommendation systems and data cleaning. It's user-friendly, stable, and suitable for beginners. Improvements could include lower pricing, video tutorials, and Python integration. It's more robust than other solutions I've used.
Data Analyst at a tech services company with 1,001-5,000 employees4.0I find RapidMiner to be valuable and easy to use, supported by a large community. However, its UI could be improved, especially compared to KNIME. We also evaluated SPSS and KNIME before deciding on RapidMiner for its interactivity.