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

Comparison Buyer's Guide

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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: March 2025).

Buyer's Guide

IBM SPSS Modeler vs. SAS Analytics

March 2025

Download the complete report

Helped 845,406 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.

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 scales. I have not run into any challenges where it will not perform."

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

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

"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."

"It is a great product for running statistical analysis."

"In the solution, I like the virtualization of data flow since it shows what goes where, which is mostly the strength of the tool."

"The quality is very good."

"Stability is good."

More IBM SPSS Modeler pros

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

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

"Modeling ones and figures, such as PROC LIFETEST, PROC LOGISTICS, PROC GPLOT. PROC FREQ and PROC MEANS, are also among the valuable features."

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

"It has improved the level of efficacy and validity of our reports."

"The team immediately resolves the issues."

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

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

More SAS Analytics pros

Cons

"C&DS will not meet our scalability needs."

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

"The time series should be improved."

"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."

"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."

"The integration with sources and visualisation needs some improvement. The scalability needs improvement."

"Time Series or forecasting needs to be easier. It is a very important feature, and it should be made easier and more automated to use. For instance, for logistic regression, binary or multinomial is used automatically based on the type of the target variable. I wish they can make Time Series easier to use in a similar way."

"Unstructured data is not appropriate for SPSS Modeler."

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."

"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."

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

"This solution should be made more user-friendly."

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

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

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

More SAS Analytics cons

Pricing and Cost Advice

"It is an expensive product."

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

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

"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."

"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."

"$5,000 annually."

"It is a huge increase to time savings."

More IBM SPSS Modeler pricing and cost advice

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

"Licensing was rather straightforward."

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

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

"Setup costs were quite reasonable."

"Prices were comparable with alternative solutions."

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

"SAS is very expensive."

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

11%

Insurance Company

Educational Organization

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 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?

The natural language querying and automated preparation of dashboards should be improved. The cost and accessibility should be improved. For a $900 USD/user/annual license you have to set up a $12,...

See all answers

What is your primary use case for SAS Analytics?

This is an application I use for data prep, data exploration, BI reporting, and some basic automated analytics.

See all answers

Comparisons

Microsoft Power BI vs IBM SPSS Modeler

Compared 29% of the time

IBM SPSS Statistics vs IBM SPSS Modeler

Compared 20% of the time

KNIME vs IBM SPSS Modeler

Compared 17% of the time

Altair RapidMiner vs IBM SPSS Modeler

Compared 7% of the time

IBM Watson Studio vs IBM SPSS Modeler

Compared 2% of the time

More IBM SPSS Modeler Competitors

KNIME vs SAS Analytics

Compared 41% of the time

IBM SPSS Statistics vs SAS Analytics

Compared 24% of the time

Weka vs SAS Analytics

Compared 21% of the time

More SAS Analytics Competitors

Product Reports

Buyer's Guide

IBM SPSS Modeler

March 2025

Download IBM SPSS Modeler product report

Buyer's Guide

Data Mining

March 2025

Download SAS Analytics product report

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

March 2025

Free Report: IBM SPSS Modeler vs. SAS Analytics

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