Altair RapidMiner vs SAP Predictive Analytics [EOL] comparison

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Altair and SAP are both solutions in the Data Science Platforms category. Additionally, 96% of Altair users are willing to recommend the solution, compared to 100% of SAP users who would recommend it.

Altair RapidMiner

Read 26 Altair RapidMiner reviews

6,131 Views
4,966 Comparison Views

96% willing to recommend

SAP Predictive Analytics [EOL]

Read 3 SAP Predictive Analytics [EOL] reviews

100% willing to recommend

Altair RapidMiner

SAP Predictive Analytics [EOL]

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Executive SummaryUpdated on Jun 3, 2026

Altair RapidMiner and SAP Predictive Analytics [EOL] are products in the predictive analytics category. Altair RapidMiner's competitive pricing and strong support give it an advantage for budget-conscious buyers, while SAP Predictive Analytics [EOL]'s advanced features may justify its higher cost for those needing robust analytics solutions.

Features: Altair RapidMiner offers easy integration, extensive third-party APIs, and strong data visualization tools. SAP Predictive Analytics [EOL] provides sophisticated automated machine learning and seamless integration with SAP platforms. Altair RapidMiner is appealing to smaller businesses for its flexibility, whereas SAP's deep features benefit enterprises.

Ease of Deployment and Customer Service: Altair RapidMiner's cloud-based deployment allows for faster implementation with minimal IT resources. SAP Predictive Analytics [EOL] requires more intensive setup due to complex functionalities. Altair RapidMiner generally provides quicker, more responsive support compared to SAP.

Pricing and ROI: Altair RapidMiner offers a lower entry cost and a shorter path to ROI, making it valuable for budget-efficient businesses. SAP Predictive Analytics [EOL], though more expensive, provides significant long-term ROI through its comprehensive analytics and integration capabilities, favoring businesses with high analysis demands.

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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

Average Rating

8.4

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Predictive Analytics (6th), Data Science Platforms (11th)

SAP Predictive Analytics [EOL]

Average Rating

8.6

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Featured Reviews

Satesh P

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.

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Gary Cook

Executive at Empowered Analytics

Enables us to forecast and pull trends and has an easy installation

My rating for SAP Predictive Analytics would be an eight out of ten. If I have to be bold, I'll probably say that we're building away hours, and we are actually putting a lot of the actual predicting stuff back into the warehouse. So running it very bi-directionally. So I'm not sure what its integration features are at the moment, but that's an area we're going to look into in the next month or so.

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

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

"It is easy to use and has a huge community that I can rely on for help. Moreover, it is interactive."

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

"The tools have a complete function for doing data."

"From my perspective as a solution architect, the core value proposition of Altair RapidMiner is that it lets organizations build, deploy, and operationalize machine learning workflows without needing a team of PhD data scientists."

"RapidMiner has a freemium pricing model so, as long as your dataset has fewer than 10,000 rows, you have free software."

"The technical support for RapidMiner is fantastic."

"The most valuable features are the Binary classification and Auto Model."

More Altair RapidMiner pros

"I have found that the solution is very stable."

"SAP Predictive Analytics is better suited for business users because it hides the complexity of the model, whereas Microsoft Azure Machine Learning provides a lot more flexibility for technical professionals to tweak the model."

"I think the features of the actual ability to forecast and pull trends and correlations has been really good."

"The most valuable features are the analytics and reporting."

"We always purchase SAP support because it is very good."

Cons

"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."

"In the Mexican or Latin American market, it's kind of pricey."

"Improve the online data services."

"The price of this solution should be improved."

"I would like to see more integration capabilities."

"I would like to see wider adoption of the RapidMiner platform by the Open Source community as a viable alternative/companion to Python and R."

"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."

"I think it's a great product but confusing in some way with regard to the user interface and integration with other tools."

More Altair RapidMiner cons

"This solution works for acquired data but not live, real-time data."

"The license fee appears to be prohibitively expensive and overly secretive, leading our clients to opt for cloud-based solutions that only charge for data storage and processing time."

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."

"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 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."

"The pricing is reasonable"

"A free trial version is available for testing out this solution."

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Top Industries

By visitors reading reviews

Manufacturing Company

13%

Financial Services Firm

10%

University

Computer Software Company

Outsourcing Company

18%

Construction Company

15%

Transportation 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	10

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...

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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...

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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...

See all answers

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Product Reports

Buyer's Guide

Altair RapidMiner

September 2026

Download Altair RapidMiner product report

Buyer's Guide

Data Science Platforms

September 2026

Download SAP Predictive Analytics [EOL] product report

Also Known As

No data available

SAP BusinessObjects Predictive Analytics, BusinessObjects Predictive Analytics, BOPA

Overview

Altair RapidMiner is a GUI-driven, code-free data science tool ideal for users seeking efficiency and user-friendliness, featuring automated data cleaning and versatile model support for diverse tasks.

Altair RapidMiner offers an accessible platform with drag-and-drop functionality, supporting multiple file formats to streamline data science workflows. It enables quick prototyping and integrates with APIs, Python, and R, enhancing user flexibility. Comprehensive documentation and tutorials support learning, while features like model fine-tuning and predictive analytics cater to advanced analysis. Enhancements in automation and deep learning, alongside improvements in data service integration and metadata handling, remain a focus for development.

What are the key features of Altair RapidMiner?

Code-Free Interface: Simplifies data science with GUI support.
Drag-and-Drop Functionality: Streamlines process setup.
Automated Data Cleaning: Saves time in data preparation.
Machine Learning Algorithms: Supports a wide range for various tasks.
API & Python/R Integration: Enhances flexibility for data projects.
Tutorials & Documentation: Provides robust learning resources.

What benefits and ROI can users expect?

Efficiency: Reduces time spent on data processing.
Flexibility: Offers adaptable integration options.
Scalability: Suited for both educational and business environments.
Usability: User-friendly interface encourages wider adoption.
Predictive Capabilities: Empowers advanced business analytics.

Industries such as telecom and finance utilize Altair RapidMiner for tasks like data preparation and forecasting. Universities employ it for education and research projects, while businesses apply it to areas such as financial crime management and market analysis. It assists companies in predicting customer behavior and analyzing pharmaceutical data, allowing seamless integration with other systems.

Altair

SAP Predictive Analytics [EOL] offered a powerful platform for creating predictive models that supported business decision-making by utilizing historical data to anticipate future trends.

SAP Predictive Analytics [EOL] was designed to integrate with existing SAP environments, allowing businesses to leverage their existing data infrastructure. It provided users with intuitive tools to automate data preparation and model management, simplifying complex analytical processes. Data scientists could efficiently build and deploy predictive models to address specific business questions. SAP emphasized ease of deployment and scalability, ensuring the platform met the needs of data-driven enterprises.

What are the key features?

Automated Model Creation: Streamlines the process of generating predictive models, reducing time and effort.
Data Preparation: Simplifies data cleaning and preparation, ensuring high-quality input for analysis.
Seamless Integration: Easily integrates with SAP environments, enhancing data accessibility.

What benefits should users consider in reviews?

Informed Decision-Making: Provides insights that help businesses make data-informed decisions.
Efficiency in Analysis: Reduces the time needed to develop and deploy predictive models.
Scalability: Supports expanding data needs as businesses grow.

In industries like manufacturing and retail, SAP Predictive Analytics [EOL] helped optimize supply chains and inventory management by forecasting demand trends. Financial sector users implemented it to enhance risk analysis and fraud detection models, providing valuable insights for mitigating potential risks.

SAP

Sample Customers

PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen

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