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Altair RapidMiner vs SAS Predictive Analytics 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 Predictive Analytics
6th
Average Rating
8.4
Reviews Sentiment
6.9
Number of Reviews
26
Ranking in other categories
Data Science Platforms (11th)
SAS Predictive Analytics
Ranking in Predictive Analytics
8th
Average Rating
7.0
Reviews Sentiment
7.6
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of September 2026, in the Predictive Analytics category, the mindshare of Altair RapidMiner is 5.6%, down from 11.5% compared to the previous year. The mindshare of SAS Predictive Analytics is 3.7%, up from 3.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Predictive Analytics Mindshare Distribution
ProductMindshare (%)
Altair RapidMiner5.6%
SAS Predictive Analytics3.7%
Other90.7%
Predictive Analytics
 

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.
it_user1139529 - PeerSpot reviewer
Data Scientist at a tech services company with 1,001-5,000 employees
Drag-and-drop functionality makes the interface easy to use, but the technical support needs to be improved
There are not many people deploying models using this solution, which is a problem. I have done some cross-development and have found that when I am building models with the open-source software, the accuracy is better. For categorical data, the models built by SAS Emailer are very complex compared to those built by the open-source version. Technical support could be improved because they take too long to answer our queries. Models that are created are a block box, and you can't see the details.

Quotes from Members

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

Pros

"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 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 data stored there. RapidMiner offers a wider range of operators than other tools like Dataiku, making it a better option for my needs."
"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."
"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"
"The data science, collaboration, and IDN are very, very strong."
"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."
"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."
"The most valuable feature is its flexibility and the ability to integrate with SAS."
"The most valuable features are forecasting and reporting."
 

Cons

"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 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 think it's a great product but confusing in some way with regard to the user interface and integration with other tools."
"It's supposedly very intuitive, and yet, I don't know where to click, honestly."
"In terms of the UI and SaaS, the user interface with KNIME is more appealing than RapidMiner."
"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."
"RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models."
"RapidMiner isn't cheap. It's a complete solution, but it's costly."
"Technical support could be improved because they take too long to answer our queries."
"If SAS were more flexible in terms of licensing then that would be good, because it costs more than other solutions."
"I think that this solution should be more compatible with other software, including open-source solutions."
 

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."
"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."
"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."
"If SAS were more flexible in terms of licensing then that would be good, because it costs more than other solutions."
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Top Industries

By visitors reading reviews
Manufacturing Company
13%
Financial Services Firm
10%
University
9%
Computer Software Company
8%
No data available
 

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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Overview

 

Sample Customers

PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen
MetLife
Find out what your peers are saying about Altair RapidMiner vs. SAS Predictive Analytics and other solutions. Updated: September 2026.
913,924 professionals have used our research since 2012.