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 18.1% mindshare in DM, compared to IBM SPSS Statistics’s 16.6% 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

968 Views
781 Comparison Views

86% willing to recommend

IBM SPSS Statistics

Read 38 IBM SPSS Statistics reviews

986 Views
657 Comparison Views

88% willing to recommend

SAS Analytics

Read 11 SAS Analytics reviews

551 Views
335 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: June 2025).

Buyer's Guide

Data Mining

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:

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 IBM SPSS Statistics is 16.6%, up from 12.9% 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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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 will scale up to anything we need."

"Our business units' capabilities with SPSS Modeler is high. They no longer waste time on modeling and algorithms, meaning they are not coding any more. For example, segmentation projects now take one to three months, rather than six months to a year, as before."

"It makes pretty good use of memory. There are algorithms take a long time to run in R, and somehow they run more efficiently in Modeler."

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

"Our go live process has been slightly enhanced compared to the previous programmatic process. There is now a faster time to production from the business end."

"Very good data aggregation."

"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."

More IBM SPSS Modeler pros

"The learning curve to using this product is not steep. The program is appropriate for those who do not have a lot of background in programming, yet have to perform basic statistical analysis."

"The solution has numerous valuable features. We particularly like custom tabs. It's very useful. We end up analyzing a lot of software data, so features related to custom tabs are really helpful."

"SPSS is quite robust and quicker in terms of providing you the output."

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

"You can quickly build models because it does the work for you."

"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."

"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."

"The best part is that they have an algorithm handbook, so you can open it up and understand how it works, and if it is useful, this is very important."

More IBM SPSS Statistics pros

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

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

"The team immediately resolves the issues."

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

"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."

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

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

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

More SAS Analytics pros

Cons

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

"When I used it in the office, back in the day, we did have some stability issues. Sometimes it just randomly crashed and we couldn't get good feedback. But when I use it for my own stuff now I don't have any problems."

"Unstructured data is not appropriate for SPSS Modeler."

"It is not integrated with Qlik, Tableau, and Power BI."

"Expensive to deploy solutions. You need to buy an extra deployment unit."

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

"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."

"I can say the solution is outdated."

More IBM SPSS Modeler cons

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

"It could provide even more in the way of automation as there are many opportunities."

"Technical support needs some improvement, as they do not respond as quickly as we would like."

"I recently moved away from SPSS and started using KNIME since it is particularly easier for students."

"The solution needs more planning tools and capabilities."

"It would be helpful if there was better documentation on how to properly use the solution. A beginner's guide on how to use the various programming functions within the product would be so useful to a lot of people. I found that everything was very confusing at first. Having clear documentation would help alleviate that."

"The product should provide more ways to import data and export results that are user-friendly for high-level executives."

"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."

More IBM SPSS Statistics cons

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

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

"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."

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

"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."

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

More SAS Analytics cons

Pricing and Cost Advice

"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 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."

"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."

"It is a huge increase to time savings."

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

More IBM SPSS Modeler pricing and cost advice

"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."

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

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

"We think that IBM SPSS is expensive for this function."

"More affordable training for new staff members."

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

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

"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."

More IBM SPSS Statistics pricing and cost advice

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

"Setup costs were quite reasonable."

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

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

"SAS is very expensive."

"Prices were comparable with alternative solutions."

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

"Licensing was rather straightforward."

More SAS Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

12%

Educational Organization

10%

Government

University

Financial Services Firm

17%

Computer Software Company

Manufacturing Company

University

Financial Services Firm

21%

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 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 25% 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 5% of the time

Dataiku vs IBM SPSS Modeler

Compared 3% of the time

More IBM SPSS Modeler Competitors

Weka vs IBM SPSS Statistics

Compared 9% of the time

TIBCO Statistica vs IBM SPSS Statistics

Compared 9% of the time

Alteryx vs IBM SPSS Statistics

Compared 8% of the time

Amazon SageMaker vs IBM SPSS Statistics

Compared 6% of the time

Anaconda vs IBM SPSS Statistics

Compared 3% of the time

More IBM SPSS Statistics Competitors

KNIME vs SAS Analytics

Compared 34% of the time

Oracle Advanced Analytics vs SAS Analytics

Compared 17% of the time

Weka vs SAS Analytics

Compared 15% of the time

More SAS Analytics Competitors

Product Reports

Buyer's Guide

IBM SPSS Modeler

June 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

June 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: June 2025.

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