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 8.5. IBM holds a 17.1% 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

1,087 Views
885 Comparison Views

86% willing to recommend

SAS Analytics

Read 10 SAS Analytics reviews

619 Views
434 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

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Helped 839,422 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 March 2025, in the Data Mining category, the mindshare of IBM SPSS Modeler is 17.1%, up from 16.7% compared to the previous year. The mindshare of SAS Analytics is 6.1%, down from 9.4% 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

"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 is very scalable for non-technical people."

"It is just a lot faster. So you do not have to write a bunch of code, you can throw that stuff on there pretty quickly and do prototyping quickly."

"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"

"The quality is very good."

"We have a local representative who specializes in SPSS. He will help us do the PoC."

"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

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

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

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

"The team immediately resolves the issues."

"The technical support is okay."

"SAS Business Intelligence is well-suited for our large corporation. We have demand for scalable and reliable insights into information which is housed in our large systems."

"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."

More SAS Analytics pros

Cons

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

"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."

"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."

"I would like better integration into the Weather Company solution. I have raised a couple of concerns about this integration and having more time series capabilities."

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

"Unstructured data is not appropriate for SPSS Modeler."

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

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

More IBM SPSS Modeler cons

"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."

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

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

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

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

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

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

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

More SAS Analytics cons

Pricing and Cost Advice

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

"It is an expensive product."

"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."

"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."

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

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

"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."

More IBM SPSS Modeler pricing and cost advice

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

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

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

"Prices were comparable with alternative solutions."

"SAS is very expensive."

"Licensing was rather straightforward."

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

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

More SAS Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

12%

Educational Organization

12%

Computer Software Company

University

Financial Services Firm

19%

Computer Software Company

11%

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.

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 19% of the time

KNIME vs IBM SPSS Modeler

Compared 17% of the time

Altair RapidMiner vs IBM SPSS Modeler

Compared 7% of the time

Databricks vs IBM SPSS Modeler

Compared 2% of the time

More IBM SPSS Modeler Competitors

KNIME vs SAS Analytics

Compared 36% of the time

IBM SPSS Statistics vs SAS Analytics

Compared 30% of the time

Weka vs SAS Analytics

Compared 21% of the time

More SAS Analytics Competitors

Product Reports

Buyer's Guide

IBM SPSS Modeler

February 2025

Download IBM SPSS Modeler product report

Buyer's Guide

Data Mining

February 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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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

March 2025

Free Report: IBM SPSS Modeler vs. SAS Analytics

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