IBM SPSS Modeler vs SAS Analytics comparison

IBM and SAS are both solutions in the Data Mining category. IBM is ranked #4 with an average rating of 6.8, while SAS is ranked #5 with an average rating of 9.0. IBM holds a 17.3% mindshare in DM, compared to SAS’s 6.1% 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

1,040 Views
854 Comparison Views

86% willing to recommend

SAS Analytics

Read 11 SAS Analytics reviews

587 Views
399 Comparison Views

94% willing to recommend

IBM SPSS Modeler

SAS Analytics

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Executive Summary

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

Find out in this report how the two Data Mining solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed IBM SPSS Modeler vs. SAS Analytics Report (Updated: April 2025).

Buyer's Guide

IBM SPSS Modeler vs. SAS Analytics

April 2025

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Helped 848,716 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

IBM SPSS Modeler

Ranking in Data Mining

4th

Average Rating

8.0

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

Data Science Platforms (13th)

SAS Analytics

Ranking in Data Mining

5th

Average Rating

9.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of April 2025, in the Data Mining category, the mindshare of IBM SPSS Modeler is 17.3%, up from 16.4% compared to the previous year. The mindshare of SAS Analytics is 6.1%, down from 9.1% 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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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."

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

"I think the code modeling features are the most valuable and without the need to write a code back with many different possibilities to choose from. And the second one is linked to the activity of the data preparation."

"It helped me in that I didn't need to write them by hand, and I could get a result in one or two minutes. That helped me a lot."

"We are creating models and putting them into production much faster than we would if we had just gone with a strict, code-based solution, like R or Python."

"We use analytics with the visual modeling capability to leverage productivity improvements."

"I was familiar with using IBM SPSS Modeler separately in the private sector before that. It's a good tool for extracting data from data warehouses, creating streams, and manipulating logic to extract final data."

"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."

More IBM SPSS Modeler pros

"The technical support is okay."

"The team immediately resolves the issues."

"It's very easy to use once you learn it."

"It is able to connect to all major platforms, and all the smaller platforms that I have come across."

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

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

"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 most valuable feature is the ability to handle large data sets."

More SAS Analytics pros

Cons

"I can say the solution is outdated."

"We have run into a few problems doing some entity matching/analytics."

"The platform that you can deploy it on needs improvement because I think it is Windows only. I do not think it can run off a Red Hat, like the server products. I am pretty sure it is Windows and AIX only."

"The product does not have a search function for tags."

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

"The challenge for the very technical data scientists: It is constraining for them."

"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."

"We would like to see better visualizations and easier integration with Cognos Analytics for reporting."

More IBM SPSS Modeler cons

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

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

"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."

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

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

"One of the things that can be simplified is self-service analytics, especially for a citizen developer or a citizen data scientist."

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

More SAS Analytics cons

Pricing and Cost Advice

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

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

"It is an expensive product."

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

"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."

"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."

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

"$5,000 annually."

More IBM SPSS Modeler pricing and cost advice

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

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

"SAS is very expensive."

"Setup costs were quite reasonable."

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

"Prices were comparable with alternative solutions."

"Licensing was rather straightforward."

"It is relatively expensive. It is not an easy software to afford."

More SAS Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

13%

Educational Organization

12%

University

Computer Software Company

Financial Services Firm

20%

Computer Software Company

12%

Educational Organization

University

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.

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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...

See all answers

What needs improvement with IBM SPSS Modeler?

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 app.

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 movements, specifically profit and loss movements.

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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 traditional securitization. Recently, I used SAS Analytics ( /products/sas-analytic...

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Comparisons

Microsoft Power BI vs IBM SPSS Modeler

Compared 28% of the time

IBM SPSS Statistics vs IBM SPSS Modeler

Compared 20% of the time

KNIME vs IBM SPSS Modeler

Compared 16% of the time

Altair RapidMiner vs IBM SPSS Modeler

Compared 7% of the time

Amazon SageMaker vs IBM SPSS Modeler

Compared 2% of the time

More IBM SPSS Modeler Competitors

KNIME vs SAS Analytics

Compared 39% of the time

IBM SPSS Statistics vs SAS Analytics

Compared 19% of the time

Weka vs SAS Analytics

Compared 16% of the time

Oracle Advanced Analytics vs SAS Analytics

Compared 13% of the time

More SAS Analytics Competitors

Product Reports

Buyer's Guide

IBM SPSS Modeler

April 2025

Download IBM SPSS Modeler product report

Buyer's Guide

Data Mining

April 2025

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Also Known As

SPSS Modeler

No data available

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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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

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

Buyer's Guide

IBM SPSS Modeler vs. SAS Analytics

April 2025

Free Report: IBM SPSS Modeler vs. SAS Analytics

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