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 18.1% mindshare in DM, compared to SAS’s 6.8% 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

968 Views
781 Comparison Views

86% willing to recommend

SAS Analytics

Read 11 SAS Analytics reviews

551 Views
335 Comparison Views

94% willing to recommend

IBM SPSS Modeler

SAS Analytics

Comparison Buyer's Guide

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Executive SummaryUpdated on May 21, 2025

SAS Analytics and IBM SPSS Modeler are key players in data analytics. SAS Analytics excels with its advanced statistical capabilities and pricing advantages, while IBM SPSS Modeler offers ease of use and flexibility, making it preferable for diverse data needs.

Features: SAS Analytics offers robust data management, advanced predictive modeling, and a comprehensive array of statistical tools. IBM SPSS Modeler provides intuitive data preparation, a highly user-friendly interface, and efficient model deployment options.

Room for Improvement: SAS Analytics could benefit from a more user-friendly interface, easier integration with other platforms, and streamlined deployment processes. IBM SPSS Modeler would improve with enhanced visual modeling capabilities, better security features, and expanded data visualization options.

Ease of Deployment and Customer Service: SAS Analytics involves a complex deployment requiring technical expertise, supported by detailed documentation. IBM SPSS Modeler allows for simple deployment with smoother integration, coupled with intuitive customer service for easier implementation.

Pricing and ROI: SAS Analytics, despite higher setup costs, offers significant long-term ROI for data-intensive projects. IBM SPSS Modeler provides competitive pricing and delivers substantial ROI through ease of use and rapid deployment, appealing as a cost-effective solution for quick analytics execution.

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

Buyer's Guide

IBM SPSS Modeler vs. SAS Analytics

June 2025

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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

4th

Average Rating

8.0

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

Data Science Platforms (14th)

SAS Analytics

Ranking in Data Mining

5th

Average Rating

9.2

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of June 2025, in the Data Mining category, the mindshare of IBM SPSS Modeler is 18.1%, up from 16.4% compared to the previous year. The mindshare of SAS Analytics is 6.8%, down from 8.4% 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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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"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."

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

"A lot of jobs that are stuck in Excel due to the huge numbers of rows are tackled pretty quickly."

"We have been able to do some predictive modeling with it"

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

"IBM was chosen because of usability. It's point and click, whereas the other out-of-the box-solution, or open-source solutions, require full-on programming and a much higher skill level."

"So far, the stability has been rock solid."

"We had an IBM Guardium service contract where we used one of their resources to help us develop our prototype. It was a good experience, but they were helpful and responsive."

More IBM SPSS Modeler pros

"The technical support is okay."

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

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

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

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

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

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

"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

"I think mapping for geographic data would also be a really great thing to be able to use."

"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."

"If IBM could add some of the popular models into the SPSS for further analysis, like popular regression models, I think that would be a helpful improvement."

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

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

"Unstructured data is not appropriate for SPSS Modeler."

"Formula writing is not straightforward for an Excel user. Totally new set of functions, which takes time to learn and teach."

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

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."

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

"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."

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

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

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

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

More SAS Analytics cons

Pricing and Cost Advice

"$5,000 annually."

"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."

"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."

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

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

More IBM SPSS Modeler pricing and cost advice

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

"Setup costs were quite reasonable."

"Licensing was rather straightforward."

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

"Prices were comparable with alternative solutions."

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

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

"SAS is very expensive."

More SAS Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

12%

Educational Organization

11%

University

Computer Software Company

Financial Services Firm

22%

Computer Software Company

10%

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?

SAS Analytics could improve in areas such as handling stress tests and workloads, as well as predicting financial movements, specifically profit and loss movements.

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

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Comparisons

Microsoft Power BI vs IBM SPSS Modeler

Compared 26% of the time

IBM SPSS Statistics vs IBM SPSS Modeler

Compared 21% of the time

KNIME vs IBM SPSS Modeler

Compared 16% of the time

Altair RapidMiner vs IBM SPSS Modeler

Compared 8% of the time

Databricks vs IBM SPSS Modeler

Compared 2% of the time

More IBM SPSS Modeler Competitors

KNIME vs SAS Analytics

Compared 37% of the time

IBM SPSS Statistics vs SAS Analytics

Compared 20% of the time

Weka vs SAS Analytics

Compared 16% of the time

Oracle Advanced Analytics vs SAS Analytics

Compared 14% of the time

More SAS Analytics Competitors

Product Reports

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IBM SPSS Modeler

June 2025

Download IBM SPSS Modeler product report

Buyer's Guide

Data Mining

May 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

Sign up for the trial
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

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

June 2025

Free Report: IBM SPSS Modeler vs. SAS Analytics

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