Altair RapidMiner vs SAS Enterprise Miner comparison

Why PeerSpot?

Altair and SAS are both solutions in the Data Science Platforms category. Altair is ranked #11 with an average rating of 7.5, while SAS is ranked #20. Altair holds a 3.3% mindshare in Data Science Platforms, compared to SAS’s 2.5% mindshare. Additionally, 96% of Altair users are willing to recommend the solution, compared to 93% of SAS users who would recommend it.

Altair RapidMiner

Read 26 Altair RapidMiner reviews

6,535 Views
5,163 Comparison Views

96% willing to recommend

SAS Enterprise Miner

Read 13 SAS Enterprise Miner reviews

3,151 Views
2,458 Comparison Views

93% willing to recommend

Altair RapidMiner

SAS Enterprise Miner

Comparison Buyer's Guide

Download the report

Executive SummaryUpdated on Mar 22, 2026

SAS Enterprise Miner and Altair RapidMiner are key competitors in the data analytics space. Altair RapidMiner seems to have the upper hand due to its flexibility and ease of integration.

Features: SAS Enterprise Miner offers comprehensive statistical analysis features, predictive modeling, and data mining capabilities. It excels in handling complex analytical tasks with its robust data mining tools and advanced statistical functions. Altair RapidMiner provides innovative data science tools, a GUI for easy model building, and supports a variety of integrations, focusing on flexibility and seamless model experimentation.

Room for Improvement: SAS Enterprise Miner could improve its user interface and ease of use for beginners, reduce its learning curve, and enhance its integration capabilities with new technologies. Altair RapidMiner could benefit from expanding its generative AI features, optimizing large dataset handling, and strengthening its community and support resources.

Ease of Deployment and Customer Service: Altair RapidMiner supports flexible deployment across on-premise, cloud, and hybrid environments, emphasizing seamless integration and data science project operationalization. Its customer service is responsive and helps ensure streamlined deployment. SAS Enterprise Miner, while reputable, has a steeper learning curve and follows a traditional support model, making deployment more complex.

Pricing and ROI: SAS Enterprise Miner typically involves higher setup costs, which might be a barrier for smaller businesses, though offering strong ROI for large-scale analytics. Altair RapidMiner offers a more affordable setup with competitive pricing and substantial ROI, focusing on cost-effectiveness and rapid deployment, making it a preferred choice for budget-conscious organizations.

To learn more, read our detailed Altair RapidMiner vs. SAS Enterprise Miner Report (Updated: September 2026).

Buyer's Guide

Altair RapidMiner vs. SAS Enterprise Miner

September 2026

Download the complete report

Helped 920,769 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

11th

Average Rating

8.4

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Predictive Analytics (6th)

SAS Enterprise Miner

Ranking in Data Science Platforms

20th

Average Rating

7.6

Reviews Sentiment

6.2

Number of Reviews

Ranking in other categories

Data Mining (7th)

Mindshare comparison

As of November 2026, in the Data Science Platforms category, the mindshare of Altair RapidMiner is 3.3%, down from 6.5% compared to the previous year. The mindshare of SAS Enterprise Miner is 2.5%, up from 1.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Mindshare Distribution
Product	Mindshare (%)
Altair RapidMiner	3.3%
SAS Enterprise Miner	2.5%
Other	94.2%

Data Science Platforms

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.

Read full review

reviewer1352853

Executive Head of analytics at a retailer with 5,001-10,000 employees

A stable product that is easy to deploy and can be used for structured and unstructured data mining

We use the solution for predictive analytics to do structured and unstructured data mining I like the way the product visually shows the data pipeline. The product must provide better integration with cloud-native technologies. I have been using the solution for 20 years. The product is very…

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, as we can take the information, tease out the attributes, and label everything, making it suitable for profiling and forecasting in any industry."

"The data science, collaboration, and IDN are very, very strong."

"Using the GUI, I can have models and algorithms drag and drop nodes."

"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."

"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 auto modeling has reduced end-of-line defect rates by approximately 18% in the first year after deploying the predictive quality models, translating directly into reduced scrap, lower rework costs, and better throughput."

"The best part of RapidMiner is efficiency."

"I've been using a lot of components from the Strategic Extension and Python Extension."

More Altair RapidMiner pros

"The setup is straightforward. Deployment doesn't take more than 30 minutes."

"Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic."

"It enables statistical modeling of data using Base SAS (another product from the same vendor) as the backbone."

"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."

"Technical support has been good, and when I called them at the start of using the product with some issues they were very helpful."

"Performance is excellent."

"Good data management and analytics."

"The data processing of the solution is very good, easy to use, both for enterprise and personal use."

More SAS Enterprise Miner pros

Cons

"I think that they should make deep learning models easier."

"It's supposedly very intuitive, and yet, I don't know where to click, honestly."

"The price of this solution should be improved."

"If they could include video tutorials, people would find that quite helpful."

"The biggest problem, not from a platform process, but from an avoidance process, is when you work in a heavily regulated environment, like banking and finance. Whenever you make a decision or there is an output, you need to bill it as an avoidance to the investigator or to the bank audit team. If you made decisions within this machine learning model, you need to explain why you did so. It would better if you could explain your decision in terms of delivery. However, this is an issue with all ML platforms. Many companies are working heavily in this area to help figure out how to make it more explainable to the business team or the regulator."

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

"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."

"Regarding Altair RapidMiner's AI capabilities, I think its governance and security are not the greatest."

More Altair RapidMiner cons

"The license is really expensive. This solution is for large corporations because not everybody can afford it."

"Price of the product"

"We really don't like the protocols the solution offers. The solution is much more complex than other options."

"While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system."

"Technical support could be improved."

"The product must provide better integration with cloud-native technologies."

"The visualization of the models is not very attractive, so the graphics should be improved."

"The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch."

More SAS Enterprise Miner cons

Pricing and Cost Advice

"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 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."

"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."

"This solution is for large corporations because not everybody can afford it."

"The solution is expensive for an individual, but for an enterprise/institution (purchasing bulk licenses), it is not a high price for the use that will come from it."

"The solution must improve its licensing models."

See which vendors are best for you

Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.

See recommendations

920,769 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Manufacturing Company

13%

Financial Services Firm

11%

University

Educational Organization

Financial Services Firm

16%

Construction Company

12%

Manufacturing Company

10%

Educational Organization

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	12
Midsize Enterprise	5
Large Enterprise	10

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	4
Large Enterprise	7

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...

See all answers

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...

See all answers

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

Ask a question

Earn 20 points

Comparisons

Alteryx One vs Altair RapidMiner

Compared 10% of the time

KNIME Business Hub vs Altair RapidMiner

Compared 9% of the time

Dataiku vs Altair RapidMiner

Compared 5% of the time

IBM SPSS Statistics vs Altair RapidMiner

Compared 5% of the time

Pentaho Business Analytics vs Altair RapidMiner

Compared 2% of the time

More Altair RapidMiner Competitors

KNIME Business Hub vs SAS Enterprise Miner

Compared 10% of the time

IBM SPSS Modeler vs SAS Enterprise Miner

Compared 9% of the time

IBM SPSS Statistics vs SAS Enterprise Miner

Compared 6% of the time

Alteryx One vs SAS Enterprise Miner

Compared 5% of the time

FICO Decision Management vs SAS Enterprise Miner

Compared 4% of the time

More SAS Enterprise Miner Competitors

Product Reports

Buyer's Guide

Altair RapidMiner

October 2026

Download Altair RapidMiner product report

Buyer's Guide

Data Mining

October 2026

Download SAS Enterprise Miner product report

Also Known As

No data available

Enterprise Miner

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

SAS Enterprise Miner enables comprehensive data management and analytics, handling extensive data volumes with diverse algorithms for model creation. Its integration and flexibility in SAS code usage make it suitable for both enterprise and personal use.

SAS Enterprise Miner is recognized for its data pipeline visualization, data processing, and statistical modeling capabilities. Its user-friendly GUI and automation support data mining tasks, decision tree creation, and clustering. However, improvements are needed in its interface visualization, affordability, technical support, and integration with languages like Python and cloud-native tech. Enhanced performance, visualization, and model development auditing, along with text analytics in the main license, are desirable upgrades. Integration with Microsoft SQL and combined offerings remains a priority.

What are SAS Enterprise Miner's most important features?

Data Management: Handles large data volumes efficiently.
Analytics: Integrates diverse algorithms for accurate model creation.
Integration: Supports flexible incorporation of SAS code.
Automation: Enhances data mining tasks through automation.
Clustering: Facilitates extensive clustering operations.

What benefits or ROI should users look for in reviews?

Performance: Delivers remarkable efficiency in data processing tasks.
Compatibility: Seamless integration with other technologies.
Flexibility: Adaptability for enterprise and personal use cases.
User-Friendly: Intuitive GUI aids in simplifying complex tasks.

SAS Enterprise Miner is applied across industries like banking, insurance, and healthcare for data mining, machine learning, and predictive analytics. It aids in activities such as text mining, fraud modeling, and forecasting model creation, handling structured and unstructured data, and performing ad hoc analysis to model business processes and analyze data clusters.

SAS

Sample Customers

PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen

Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare

Buyer's Guide

Altair RapidMiner vs. SAS Enterprise Miner

September 2026

Free Report: Altair RapidMiner vs. SAS Enterprise Miner

Find out what your peers are saying about Altair RapidMiner vs. SAS Enterprise Miner and other solutions. Updated: September 2026.

DOWNLOAD NOW

920,769 professionals have used our research since 2012.

See our Altair RapidMiner vs. SAS Enterprise Miner report.

See our list of best Data Science Platforms vendors.

We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.