IBM SPSS Modeler vs IBM SPSS Statistics vs SAS Analytics comparison

IBM SPSS Modeler and IBM SPSS Statistics are both solutions in the Data Mining category. IBM SPSS Modeler is ranked #4 with an average rating of 6.8, while IBM SPSS Statistics is ranked #3 with an average rating of 8.7. IBM SPSS Modeler holds a 17.6% mindshare in DM, compared to IBM SPSS Statistics’s 16.5% mindshare. Additionally, 86% of IBM SPSS Modeler users are willing to recommend the solution, compared to 88% of IBM SPSS Statistics users who would recommend it.

IBM SPSS Modeler

Read 39 IBM SPSS Modeler reviews

1,040 Views
854 Comparison Views

86% willing to recommend

IBM SPSS Statistics

Read 38 IBM SPSS Statistics reviews

1,068 Views
701 Comparison Views

88% willing to recommend

SAS Analytics

Read 11 SAS Analytics reviews

587 Views
399 Comparison Views

94% willing to recommend

IBM SPSS Modeler

IBM SPSS Statistics

SAS Analytics

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between IBM SPSS Modeler, IBM SPSS Statistics, and SAS Analytics 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: April 2025).

Buyer's Guide

Data Mining

April 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:

Mindshare comparison

As of May 2025, in the Data Mining category, the mindshare of IBM SPSS Modeler is 17.6%, up from 16.3% compared to the previous year. The mindshare of IBM SPSS Statistics is 16.5%, up from 12.4% compared to the previous year. The mindshare of SAS Analytics is 6.6%, down from 8.9% 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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Laurence Moseley

Emeritus Professor of Health Services Research at University of South Wales

Delivers reliable results for academic research and keeps you close to your data.

SPSS is perfectly adequate if all you want are some results. If you only need the results, you do not require the trail of evidence on how you obtained those results. I mainly used it for cross tabs, correlation, regression, chi-squared tests, and similar analyses often seen in published papers; I used it for my papers as well. For wider uses I find Knime keeps me in touch with my data, however much I transform them.

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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 gives you a GUI interface, which is a lot more user-friendly and easier to use compared to writing R scripts or Python."

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

"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."

"Some basic form of feature engineering for classification models. This really quickens the model development process."

"Automated modelling, classification, or clustering are very useful."

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

More IBM SPSS Modeler pros

"The most valuable feature is the user interface because you don't need to write code."

"SPSS is perfectly adequate if all you want are some results."

"It offers very good visualization."

"Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files."

"It is a modeling tool with helpful automation."

"The SPSS interface is very accessible and user-friendly. It's really easy to get information in it. I've shared it with experts and beginners, and everyone can navigate it."

"The most valuable features are the solution is easy to use, training new users is not difficult, and our usage is comprehensive because the whole service is beneficial."

"It has helped our analyst unit deliver work with more transparency and confidence, given that we can always view the dataset in totality, after each step of data transformation."

More IBM SPSS Statistics pros

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

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

"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."

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

"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."

"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."

More SAS Analytics pros

Cons

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

"The biggest issue with the visual modeling capability is that we can't extract the SQL code under the hood."

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

"When you are not using the product, such as during the pandemic where we had worldwide lockdowns, you still have to pay for the licensing."

"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."

"Dimension reduction should be classified separately."

"I can say the solution is outdated."

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

More IBM SPSS Modeler cons

"Needs more statistical modelling functions."

"I feel that when it comes to conducting multiple analyses, there could be more detailed information provided. Currently, the software gives a summary and an overview, but it would be beneficial to have specific details for each product or variable."

"Better documentation on how to use macros."

"I know that SPSS is a statistical tool but it should also include a little bit of analytical behavior. You can call it augmented analysis or predictive analysis. The bottom line is it should have more graphical and analytical capabilities."

"There is a learning curve; it's not very steep, but there is one."

"Perhaps in terms of visualization. It's not really easy to do some data visualization, just simple, descriptive analysis in SPSS. I think that could be an area for improvement."

"IBM SPSS Statistics does not keep you close to your data like KNIME."

"SPSS slows down the computer or the laptop if the data is huge; then you need a faster computer."

More IBM SPSS Statistics cons

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

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

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

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

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

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

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

"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."

More SAS Analytics cons

Pricing and Cost Advice

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

"$5,000 annually."

"It is an expensive product."

"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."

"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."

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

More IBM SPSS Modeler pricing and cost advice

"Our licence is on a yearly renewal basis. While pricing is not the primary concern in our evaluation, as products are assessed by whether they can meet our user needs and expertise, the cost can be a limiting factor in the number of licences we procure."

"The price of this solution is a little bit high, which was a problem for my company."

"I rate the tool's pricing a five out of ten."

"SPSS is an expensive piece of software because it's incredibly complex and has been refined over decades, but I would say it's fairly priced."

"While the pricing of the product may be higher, the accompanying service and features justify the investment."

"The price of IBM SPSS Statistics could improve."

"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."

"It's quite expensive, but they do a special deal for universities."

More IBM SPSS Statistics pricing and cost advice

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

"Prices were comparable with alternative solutions."

"Setup costs were quite reasonable."

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

"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."

"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

11%

University

Computer Software Company

Financial Services Firm

17%

Computer Software Company

Manufacturing Company

University

Financial Services Firm

20%

Computer Software Company

11%

Educational Organization

Insurance 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 IBM SPSS Statistics?

The software offers consistency across multiple research projects helping us with predictive analytics capabilities.

See all answers

What is your experience regarding pricing and costs for IBM SPSS Statistics?

SPSS is horrendously expensiver. On a laptop Knime is free of charge (Windows, Mac, Linux)

See all answers

What needs improvement with IBM SPSS Statistics?

Better guidance both in producing programs and interpreting their output.

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

Comparisons

Microsoft Power BI vs IBM SPSS Modeler

Compared 27% of the time

KNIME vs IBM SPSS Modeler

Compared 16% of the time

Altair RapidMiner vs IBM SPSS Modeler

Compared 8% of the time

Alteryx vs IBM SPSS Modeler

Compared 6% of the time

Microsoft Azure Machine Learning Studio vs IBM SPSS Modeler

Compared 2% of the time

More IBM SPSS Modeler Competitors

TIBCO Statistica vs IBM SPSS Statistics

Compared 10% of the time

Weka vs IBM SPSS Statistics

Compared 10% of the time

Alteryx vs IBM SPSS Statistics

Compared 8% of the time

Amazon SageMaker vs IBM SPSS Statistics

Compared 7% of the time

Dataiku vs IBM SPSS Statistics

Compared 3% of the time

More IBM SPSS Statistics Competitors

KNIME vs SAS Analytics

Compared 40% of the time

Weka vs SAS Analytics

Compared 15% 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

IBM SPSS Statistics

April 2025

Download IBM SPSS Statistics product report

Buyer's Guide

Data Mining

April 2025

Download SAS Analytics product report

Also Known As

SPSS Modeler

SPSS Statistics

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.

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https://www.ibm.com/products/spss-modeler/pricing

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IBM

IBM SPSS Statistics is a powerful data mining solution that is designed to aid business leaders in making important business decisions. It is designed so that it can be effectively utilized by organizations across a wide range of fields. SPSS Statistics allows users to leverage machine learning algorithms so that they can mine and analyze data in the most effective way possible.

IBM SPSS Statistics Benefits

Some of the ways that organizations can benefit by choosing to deploy IBM SPSS Statistics include:

Ease of use. SPSS Statistics enables users to simply and intuitively take control of their statistical needs. The solution is designed so that analysts who do not know how to code can easily make full use of the various tools and capabilities that SPSS Statistics has to offer. Its command language is so straightforward that it does not require users to undergo special training before they use it.

Comprehensive and flexible build. SPSS Statistics is designed to be both a comprehensive and highly flexible analytics solution. It enables users to utilize a variety of integrations that make it easy for users to add features that they might feel they are missing.

Automation. SPSS Statistics makes it simple for users to automate basic tasks that they might otherwise devote too much time worrying about. Tasks like calculation or data gathering can be delegated to the system while more conceptual tasks like data analysis are given to an organization’s analysts to handle.

IBM SPSS Statistics Features

Intuitive user interface. SPSS Statistics enables users to deploy an intuitive interface that makes the process of system management simple. Among the other components of this interface is a drag-and-drop feature that makes analysis and management possible for anyone who wants to use it.

Advanced data visualizations. Analysts that employ SPSS Statistics gain access to tools that empower them to create and export data visualizations. These visualizations can be formatted in many different ways depending on what the user needs.

Local data storage. SPSS Statistics has the ability to securely store data on a user’s computer. This enables them to add layers of security that would not necessarily be present if the data was stored in the cloud.

Reviews from Real Users

IBM SPSS Statistics is a highly effective solution that stands out when compared to many of its competitors. Two major advantages it offers are the wealth of functionalities that it provides and its high level of accessibility.

An Emeritus Professor of Health Services Research at a university writes, "The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can in a multidimensional setup space. It's the multidimensional space facility that is most useful."

A Director of Systems Management & MIS Operations at a university, says, “The SPSS interface is very accessible and user-friendly. It's really easy to get information from it. I've shared it with experts and beginners, and everyone can navigate it.”

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

LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA

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

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

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