IBM SPSS Modeler vs SAS Enterprise Miner comparison

IBM and SAS are both solutions in the Data Mining category. IBM is ranked #3 with an average rating of 8.0, while SAS is ranked #7. IBM holds a 18.9% mindshare in DM, compared to SAS’s 4.8% mindshare. Additionally, 86% of IBM users are willing to recommend the solution, compared to 93% of SAS users who would recommend it.

IBM SPSS Modeler

Read 40 IBM SPSS Modeler reviews

2,814 Views
1,379 Comparison Views

86% willing to recommend

SAS Enterprise Miner

Read 13 SAS Enterprise Miner reviews

1,291 Views
400 Comparison Views

93% willing to recommend

IBM SPSS Modeler

SAS Enterprise Miner

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

SAS Enterprise Miner and IBM SPSS Modeler are key players in predictive analytics. IBM SPSS Modeler gains an edge with its extensive feature set and intuitive use, whereas SAS Enterprise Miner excels in data management.

Features: SAS Enterprise Miner features robust data handling, intricate data preparation, and integration with SAS programming for enhanced flexibility. IBM SPSS Modeler offers intuitive visual modeling, an extensive algorithm library, and easy integration with third-party tools like Python and R for streamlined tasks.

Room for Improvement: SAS Enterprise Miner could enhance its response time in customer support, improve its initial setup complexity, and expand its cloud capabilities. IBM SPSS Modeler can improve on its heavy initial investment requirement, refine its model customization features, and further develop its visual modeling strength compared to standalone visualization tools.

Ease of Deployment and Customer Service: SAS Enterprise Miner offers flexible deployment options, both on-premises and cloud-based, with generally reliable customer support. IBM SPSS Modeler provides streamlined cloud integration and proactive customer service that is well-received by users.

Pricing and ROI: SAS Enterprise Miner demands a substantial initial investment yet promises high ROI for large-scale projects. IBM SPSS Modeler, while also costly, often delivers faster ROI due to its user-friendly implementation and operational versatility. Pricing structures should be considered based on specific business needs.

To learn more, read our detailed IBM SPSS Modeler vs. SAS Enterprise Miner Report (Updated: March 2026).

Buyer's Guide

IBM SPSS Modeler vs. SAS Enterprise Miner

March 2026

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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

IBM SPSS Modeler

Ranking in Data Mining

3rd

Ranking in Data Science Platforms

12th

Average Rating

8.0

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

No ranking in other categories

SAS Enterprise Miner

Ranking in Data Mining

7th

Ranking in Data Science Platforms

24th

Average Rating

7.6

Reviews Sentiment

6.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of March 2026, in the Data Mining category, the mindshare of IBM SPSS Modeler is 18.9%, up from 17.1% compared to the previous year. The mindshare of SAS Enterprise Miner is 4.8%, up from 4.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining Mindshare Distribution
Product	Mindshare (%)
IBM SPSS Modeler	18.9%
SAS Enterprise Miner	4.8%
Other	76.3%

Data Mining

Featured Reviews

Prof. Dr. Rudolf Bisping

Business Owner at SASS GmbH

Support and flexibility enable effective project initiation and meet customer needs but deployment requires enhancement

The customer comes to you and says they want to deploy it and make a production out of this, which is very difficult and expensive with IBM SPSS Modeler. With MATLAB, there is no problem. I have a solution, and then I convert my MATLAB solution to C programming language. This I can deploy, and I can check it, and it is MISRA compatible. It is very easy to deploy it, to go from MATLAB to C or C++, which is actually needed in the car industry. In the car industry, they want to have it in the hardware. You cannot put MATLAB or IBM SPSS Modeler in the hardware of a car, but with C, there is no problem with a microcontroller. They can shoot it into the microcontroller, and I can check it with Polyspace, and it is MISRA compatible, which is an industrial standard. There is nothing similar in IBM SPSS Modeler. I made solutions with IBM SPSS Modeler, and then the customer said they wanted to make a production out of it, and it was not possible. I stopped with IBM SPSS Modeler 18. It is now 18.6 from what I know at the moment. I do not believe that there is a possibility to design a graphic user interface with it. It is itself a graphic user interface, where you put all sorts of little icons into the display.

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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…

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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

"You take two quarters and compare them and this tool is ideal because it gives you a lot of visibility on the before and after."

"SPSS Modeler is a friendly interface for a beginner user."

"It handles large data better than the previous system that we were using, which was basically Excel and Access. We serve upwards of 300,000 parts over a 150 regions and we need to crunch a lot of numbers."

"We are using it either for workforce deployment or to improve our operations."

"It's a very good and reasonably priced solution."

"We have full control of the data handling process."

"The benefits are that this product makes us a more efficient sales staff, reducing the inefficiencies in the buying patterns of our customers by calling them when we know they're ready to order, instead of waiting for them to call us."

"Our business units' capabilities with SPSS Modeler is high. They no longer waste time on modeling and algorithms, meaning they are not coding any more. For example, segmentation projects now take one to three months, rather than six months to a year, as before."

More IBM SPSS Modeler pros

"Good data management and analytics."

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

"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."

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

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

"Overall it is a good solution."

"he solution is scalable."

"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, and the results and the ensembles are fantastic."

More SAS Enterprise Miner pros

Cons

"I would not rate the technical support very well. The technicians have accents. When you do find someone, it is very hard to get somebody able to answer the technical questions."

"There are performance issues. Extracting data from many combined tables can take hours and occasionally crash the server due to memory leaks. This performance problem bothers people. The performance issue seems to be related to the server. We design streams on the client and submit them to the server, which generates a large SQL statement. There are two potential bottlenecks: one in the server and another in data extraction. I'm unsure about the exact mechanics of data splitting when fetching from the database."

"It is very good, but slow. The slowness may be because we have not finalized all the background information in SPSS. It still needs some tweaking."

"Regarding visual modeling, it is not the biggest strength of the product, although from what I hear in the latest release it's going to be a lot stronger. That, to me, has always been the biggest flaw in using this. It's very difficult to get good visualization."

"When I used it in the office, back in the day, we did have some stability issues. Sometimes it just randomly crashed and we couldn't get good feedback. But when I use it for my own stuff now I don't have any problems."

"Customer support is hard to contact."

"When I do clustering, I want to try a different stream, but currently the only thing that I can really pick is averaging."

"Setup is a little problematic for desktop. A nightmare for server."

More IBM SPSS Modeler cons

"The initial setup is challenging if doing it for the first time."

"The solution is much more complex than other options."

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

"The ease of use can be improved. When you are new it seems a bit complex."

"The preparation of both the mining and modeling process could be improved. The solution requires data and will reflect data, but the preparation of the data is not useful for end-users; we ended up having to do the preparation in another tool."

"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."

"The solution is quite expensive. The pricing is too high."

"Plus it is prohibitively expensive and is not available with perpetual licensing."

More SAS Enterprise Miner cons

Pricing and Cost Advice

"If you are in a university and the license is free then you can use the tool without any charges, which is good."

"Having in mind all four tools from Garner’s top quadrant, the pricing of this tool is competitive and it reflects the quality that it offers."

"It got us a good amount of money with quick and efficient modeling."

"When you are close to end of quarter, IBM and its partners can get you 60% to 70% discounts, so literally wait for the last day of the quarter for the best prices. You may feel like you are getting robbed if you can't receive a good discount."

"It is an expensive product."

"$5,000 annually."

"Its price is okay for a company, but for personal use, it is considered somewhat expensive."

"This tool, being an IBM product, is pretty expensive."

More IBM SPSS Modeler pricing and cost advice

"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."

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Top Industries

By visitors reading reviews

Government

11%

Financial Services Firm

10%

University

Outsourcing Company

Financial Services Firm

20%

Educational Organization

11%

Manufacturing Company

10%

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	9
Midsize Enterprise	4
Large Enterprise	32

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 IBM SPSS Modeler?

The government has funds and a budget, it's hard to say if it's expensive or cheap. In Canada, they have a yearly budget. They used to encourage people to use the modeler for development. If ten us...

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What needs improvement with IBM SPSS Modeler?

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What is your primary use case for IBM SPSS Modeler?

I have been using IBM SPSS Modeler for a long time. I am using IBM SPSS Modeler mainly for ETL. Sometimes I use it to compare the results of the modeling as compared to MATLAB. MATLAB is the main t...

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Compared 7% of the time

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Compared 6% of the time

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Compared 5% of the time

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Product Reports

Buyer's Guide

IBM SPSS Modeler

March 2026

Download IBM SPSS Modeler product report

Buyer's Guide

Data Mining

February 2026

Download SAS Enterprise Miner product report

Also Known As

SPSS Modeler

Enterprise Miner

Overview

IBM SPSS Modeler is an extensive predictive analytics platform that is designed to bring predictive intelligence to decisions made by individuals, groups, systems and the enterprise. By providing a range of advanced algorithms and techniques that include text analytics, entity analytics, decision management and optimization, SPSS Modeler can help you consistently make the right decisions from the desktop or within operational systems.

Buy
https://www.ibm.com/products/spss-modeler/pricing

Sign up for the trial
https://www.ibm.com/account/reg/us-en/signup?formid=urx-19947

IBM

SAS Enterprise Miner is a solution to create accurate predictive and descriptive models on large volumes of data across different sources in the organization. SAS Enterprise Miner offers many features and functionalities for the business analysts to model their data. Some of the business applications are for detecting fraud, minimizing risk, resource demands, reducing asset downtime, campaigns and reduce customer attrition.

SAS

Sample Customers

Reisebªro Idealtours GmbH, MedeAnalytics, Afni, Israel Electric Corporation, Nedbank Ltd., DigitalGlobe, Vodafone Hungary, Aegon Hungary, Bureau Veritas, Brammer Group, Florida Department of Juvenile Justice, InSites Consulting, Fortis Turkey

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

Buyer's Guide

IBM SPSS Modeler vs. SAS Enterprise Miner

March 2026

Free Report: IBM SPSS Modeler vs. SAS Enterprise Miner

Find out what your peers are saying about IBM SPSS Modeler vs. SAS Enterprise Miner and other solutions. Updated: March 2026.

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