IBM SPSS Modeler vs SAS Analytics vs SAS Enterprise Miner comparison

IBM and SAS are both solutions in the Data Mining category. IBM is ranked #4 with an average rating of 7.0, while SAS is ranked #5 with an average rating of 9.0. IBM holds a 17.9% mindshare in DM, compared to SAS’s 7.3% mindshare. Additionally, 86% of IBM users are willing to recommend the solution, compared to 94% of SAS users who would recommend it.

IBM SPSS Modeler

Read 39 IBM SPSS Modeler reviews

2,280 Views
935 Comparison Views

86% willing to recommend

SAS Analytics

Read 11 SAS Analytics reviews

555 Views
555 Comparison Views

94% willing to recommend

SAS Enterprise Miner

Read 13 SAS Enterprise Miner reviews

842 Views
278 Comparison Views

93% willing to recommend

IBM SPSS Modeler

SAS Analytics

SAS Enterprise Miner

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between IBM SPSS Modeler, SAS Analytics, and SAS Enterprise Miner based on real PeerSpot user reviews.

Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining.

To learn more, read our detailed Data Mining Report (Updated: June 2025).

Buyer's Guide

Data Mining

June 2025

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Helped 862,077 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:

Mindshare comparison

As of July 2025, in the Data Mining category, the mindshare of IBM SPSS Modeler is 17.9%, up from 16.3% compared to the previous year. The mindshare of SAS Analytics is 7.3%, down from 7.8% compared to the previous year. The mindshare of SAS Enterprise Miner is 4.7%, up from 4.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining

Featured Reviews

PeterHuo

Application Architect at Canada Border Services Agency

Good tool for extracting data from data warehouses, creating streams, and manipulating logic to extract final data

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. When streams become larger, performance bottlenecks may occur in the IBM SPSS Modeler server or the database. Sometimes the server crashes and needs to be restarted to release memory on both sides. I'm not sure exactly where the problem is caused, as I focus on stream design rather than server issues. The problem could be on the IBM SPSS Modeler server and database.

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AltanAtabarut

Solution Consulting, Growth, Analytics at Akinon

Good interactive reports and dashboards but expensive to run

You need to constantly jump from data prep to visualization, then back to data for fixing quality, enriching, and visualizing again. Then you start modeling and need to switch back and forth again. Eventually, you have to democratize the results so that anyone can look and interactively question the underlying insights. For all of these purposes - data to BI or data to AI to BI - it is never a linear one way relationship; it's rather a closed loop for continuous analysis monitoring and sharing. If used this way, SAS Visual analytics can enable continuous improvement and innovation in a corporation.

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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

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

"The most valuable features of the IBM SPSS Modeler are visual programming, you don't have to write any code, and it is easy to use. 90 to 95 percent of the use cases, you don't have to fine-tune anything. If you want to do something deeper, for example, create a better neural network, then you have to go into the features and try to fine-tune them. However, the default selection which is made by the tool, it's very practical and works well."

"We have integration where you can write third-party apps. This sort of feature opens it up to being able to do anything you want."

"I think it is the point and drag features that are the most valuable. You can simply click at the windows, and then pull up the functions."

"The supervised models are valuable. It is also very organized and easy to use."

"It works fine. I have not had any stability issues; it is always up."

"It is pretty scalable."

"It continues to be a very flexible platform, so that it handles R and Python and other types of technology. It seems to be growing with additional open-source movement out there on different platforms."

More IBM SPSS Modeler pros

"They have provided virtually everything we have needed to accomplish our task, as well as continuously improving our accuracy."

"I use SAS daily to analyze data, produce reports, and other outputs."

"All of the data analytics features in SAS Analytics are valuable to us since we're using them daily across our entire analytics team."

"The technical support is okay."

"It has also been around for an extremely long time, has a strong history, and good market penetration."

"It has facilitated timely analysis results with quality work and meaningful output."

"The team immediately resolves the issues."

"I use it to replicate our entire financial system to verify/duplicate calculations."

More SAS Analytics pros

"The solution is able to handle quite large amounts of data beautifully."

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

"The solution is very good for data mining or any mining issues."

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

"The technical support is very good."

"I like the way the product visually shows the data pipeline."

"The most valuable feature is the decision tree creation."

More SAS Enterprise Miner pros

Cons

"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."

"It would be beneficial if the tool would include more well-known machine learning algorithms."

"Initial setup of the software was complex, because of our own problems within the government."

"Requires more development."

"I can say the solution is outdated."

"It would be helpful if SPSS supported open-source features, for example, embedding R or Python scripts in SPSS Modeler."

"The time series should be improved."

"I understand that it takes some time to incorporate some of the new algorithms that have come out in the last few months, in the literature. For example, there is an algorithm based on how ants search for food. And there are some algorithms that have now been developed to complement rules. So that's one of the things that we need to have incorporated into it."

More IBM SPSS Modeler cons

"The training for SAS Business Intelligence is often difficult to arrange. It is often cancelled due to not enough people being enrolled."

"Support at universities used to be limited, but I hear this is changing."

"The graphing and visualization features could be enhanced, in my opinion. I would especially stress improving the visualization capabilities."

"They could enhance the AI capabilities of the product."

"The installation could also be easier, and the price could be better."

"The natural language querying and automated preparation of dashboards should be improved."

"Once a SAS figure is produced one would like to modify things, such as titles, legends, and incorporate risk sets as a footer on the plots."

"I would like to see their interface to R added to either Base SAS or SAS Analytics."

More SAS Analytics cons

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

"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 much more complex than other options."

"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."

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

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

"Virtualization could be much better."

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

More SAS Enterprise Miner cons

Pricing and Cost Advice

"I am using the free version of IBM SPSS Modeler, it is the educational edition version."

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

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

"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 users use the server with ten licenses, it runs faster. But if forty users use the same appliance, everything slows down. People then think it's not easy to do things and prefer using remote tools like Python to extract data from the database. It's not about being expensive or cheap, but about people's knowledge and experience in how to do the work."

"The scalability was kind of limited by our ability to get other people licenses, and that was usually more of a financial constraint. It's expensive, but it's a good tool."

"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."

"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."

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

More IBM SPSS Modeler pricing and cost advice

"The cost for SAS Business Intelligence can prove to be a little prohibitive."

"I think that the cost-benefit ratio is okay."

"Setup costs were quite reasonable."

"SAS is very expensive."

"I rate the product’s pricing a one out of ten."

"Licensing was rather straightforward."

"Our licensing covers the usage for around 50 data analysts."

"Prices were comparable with alternative solutions."

More SAS Analytics pricing and cost advice

"The solution must improve its licensing models."

"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."

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

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Top Industries

By visitors reading reviews

Financial Services Firm

12%

Educational Organization

11%

Government

University

Financial Services Firm

19%

Computer Software Company

11%

Insurance Company

Educational Organization

Financial Services Firm

27%

University

10%

Educational Organization

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about IBM SPSS Modeler?

Compared to other tools, the product works much easier to analyze data without coding.

See all answers

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 bud...

See all answers

What needs improvement with IBM SPSS Modeler?

There are performance issues. Extracting data from many combined tables can take hours and occasionally crash the ser...

See all answers

What do you like most about SAS Analytics?

I like that it is quickly embedding interactive reports and dashboards into a website, Outlook Mail, or even a mobile...

See all answers

What needs improvement with SAS Analytics?

SAS Analytics could improve in areas such as handling stress tests and workloads, as well as predicting financial mov...

See all answers

What is your primary use case for SAS Analytics?

I use SAS Analytics ( /products/sas-analytics-reviews ) in my work to analyze data, such as selecting credits for tra...

See all answers

What do you like most about SAS Enterprise Miner?

I like the way the product visually shows the data pipeline.

See all answers

What is your experience regarding pricing and costs for SAS Enterprise Miner?

The solution must improve its licensing models. It bundles all the products into smaller products. We can only have a...

See all answers

What needs improvement with SAS Enterprise Miner?

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

See all answers

Comparisons

Microsoft Power BI vs IBM SPSS Modeler

Compared 25% of the time

IBM SPSS Statistics vs IBM SPSS Modeler

Compared 22% of the time

KNIME vs IBM SPSS Modeler

Compared 15% of the time

Altair RapidMiner vs IBM SPSS Modeler

Compared 7% of the time

SAS Visual Analytics vs IBM SPSS Modeler

Compared 3% of the time

More IBM SPSS Modeler Competitors

KNIME vs SAS Analytics

Compared 34% of the time

IBM SPSS Statistics vs SAS Analytics

Compared 18% of the time

Oracle Advanced Analytics vs SAS Analytics

Compared 17% of the time

Weka vs SAS Analytics

Compared 14% of the time

More SAS Analytics Competitors

KNIME vs SAS Enterprise Miner

Compared 25% of the time

SAS Visual Analytics vs SAS Enterprise Miner

Compared 21% of the time

Altair RapidMiner vs SAS Enterprise Miner

Compared 19% of the time

TIBCO Data Science vs SAS Enterprise Miner

Compared 8% of the time

MathWorks Matlab vs SAS Enterprise Miner

Compared 8% of the time

More SAS Enterprise Miner Competitors

Product Reports

Buyer's Guide

IBM SPSS Modeler

July 2025

Download IBM SPSS Modeler product report

Buyer's Guide

Data Mining

June 2025

Download SAS Analytics product report

Buyer's Guide

Data Mining

June 2025

Download SAS Enterprise Miner product report

Also Known As

SPSS Modeler

No data available

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

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https://www.ibm.com/account/reg/us-en/signup?formid=urx-19947

IBM

SAS was founded in 1976 and actually began as a project at North Carolina State University to analyze agriculture research. It has since become a global company that is recognized for its innovation in data analytics and business intelligence. SAS is redefining what's possible with data analytics through greater efficiency, strong information value chains, effective collaboration tools, and state-of-the-art visualization software. SAS Analytics is designed for use in a variety of industries including government, manufacturing, higher education, defense & security, banking, automotive, communications, and much more. SAS Analytics is a business intelligence (BI) solution that has the ability to reveal patterns and anomalies in data, identify relationships and different variables, and predict future outcomes. Users of SAS Analytics will benefit from making more sound, better informed business decisions based on company data and market trends. Data mining, data visualization, text analytics, forecasting, statistical analysis, and more are all available through SAS Analytics. Staples, which boasts $27 billion in sales across the globe, has a business philosophy that prioritizes customer loyalty and satisfaction. In order to better engage their customers, Staples utilizes SAS Analytics to plan finely tuned marketing campaigns. Through forecasting and advanced analytics, Staples has been able to rely on fewer contractors, and cut their marketing budget, while improving their customer retention rate.

SAS

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

Aegon, Alberta Parks, Amway China, Axel Springer, Bank of America, Belgium Special Tax, CAP Index, CareSource, CBE Group, Cemig, Center for Responsible Lending, CESCE, Ceska sporitelna, Chantecler, Chico's, Chubb Group of Insurance Companies, CIGNA Thailand, City of Wiesbaden, Germany, Confused.com, Creditreform, Des Moines Area Community College, Deutsche Lufthansa, Directorate of Economics and Statistics, DIRECTV, Dow Chemical Company, Dow Chemical Company, Dun & Bradstreet, EDF Energy, Electrabel GDF SUEZ, ERGO Insurance Group, Erste Bank Croatia, Farmers Mutual Group, Finnair, Florida Department of Corrections, Geneia, Generali Hellas, Genting Malaysia Berhad, Grameenphone, Grandi Salumifici Italiani, HealthPartners, Highmark, Hong Kong Efficiency Unit, HP, Hyundai Securities, Illinois Department of Healthcare and Family ServicesInc Research, ING-DiBa, Institut Pertanian Bogor, InterContinental Hotels Group (IHG), IOM, Kelley Blue Book, Lenovo, Lillebaelt Hospital, Los Angeles County, Maspex Wadowice Group, National Bank of Greece, New Zealand Ministry of Health, New Zealand Ministry of Social Development, Nippon Paper, NMIMS, North Carolina Department of Transportation, North Carolina Office of Information Technology Services, Northern Virginia Electric Cooperative (NOVEC), Oberweis Dairy, ODEC, Ohio Mutual Insurance Group, Oklahoma State University, OneBeacon, Orange Business Services, Orange County Child Support Services, Organic, Orlando Magic, OTP Bank, Plano Independent School District, Project Odyssey, Royal Society for the Protection of Birds, RSA Canada, SCAD, Scotiabank, Singapore National Library Board, Sobeys Inc., SRA International, Staples, Statistics Estonia, Swisscom, SymphonyIRI Group, Telecom Italia, Telef‹nica O2, Town of Cary, Transitions Optical, TrueCar, Turkcell Superonline, UniCredit Bank Serbia, University of Alabama, University of Missouri, USDA National Agricultural Statistics Service

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

Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining. Updated: June 2025.

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