IBM SPSS Statistics vs SAS Analytics comparison

IBM and SAS are both solutions in the Data Mining category. IBM is ranked #3 with an average rating of 9.2, while SAS is ranked #5 with an average rating of 9.0. IBM holds a 15.9% mindshare in DM, compared to SAS’s 7.3% mindshare. Additionally, 88% of IBM users are willing to recommend the solution, compared to 94% of SAS users who would recommend it.

IBM SPSS Statistics

Read 38 IBM SPSS Statistics reviews

992 Views
642 Comparison Views

88% willing to recommend

SAS Analytics

Read 11 SAS Analytics reviews

555 Views
329 Comparison Views

94% willing to recommend

IBM SPSS Statistics

SAS Analytics

Comparison Buyer's Guide

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Executive SummaryUpdated on May 21, 2025

SAS Analytics and IBM SPSS Statistics compete in the data analysis category. IBM SPSS Statistics tends to have the upper hand due to superior features despite SAS Analytics offering better pricing and support.

Features: SAS Analytics is recognized for advanced analytics capabilities, predictive modeling, and handling large data sets. Meanwhile, IBM SPSS focuses on statistical analysis, complex data manipulation, and is user-friendly for non-technical users.

Room for Improvement: SAS could enhance its user interface to be more intuitive, improve integration with emerging data platforms, and offer a more affordable subscription model. IBM SPSS might benefit from expanding customization options, increasing processing speed for larger data sets, and refining their customer support response times.

Ease of Deployment and Customer Service: SAS offers a customizable deployment with smooth setup due to flexible options and integrated support. IBM SPSS provides a standard deployment with easily accessible support, focusing on quick implementation.

Pricing and ROI: SAS Analytics has higher initial costs but offers beneficial ROI with its robust capabilities. IBM SPSS operates on a subscription model, giving short-term affordability and value with a comprehensive feature set.

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

Buyer's Guide

IBM SPSS Statistics 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 Statistics

Ranking in Data Mining

3rd

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Data Science Platforms (8th)

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 July 2025, in the Data Mining category, the mindshare of IBM SPSS Statistics is 15.9%, up from 13.4% compared to the previous year. The mindshare of SAS Analytics is 7.3%, down from 7.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining

Featured Reviews

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

"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."

"Capability analysis is one of the main and valuable functions. We also do some hypothesis testing in Minitab and summary stats. These are the functions that we find very useful."

"in terms of the simplicity, I think the SPSS basic can handle it."

"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."

"The most valuable features are the small learning curve and its ability to hold a lot of data."

"It offers very good visualization."

"Most of the product features are good but I particularly like the linear regression analysis."

"It has the ability to easily change any variable in our research."

More IBM SPSS Statistics pros

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

"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."

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

"The technical support is okay."

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

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

More SAS Analytics pros

Cons

"I'd like to see them use more artificial intelligence. It should be smart enough to do predictions and everything based on what you input."

"The design of the experience can be improved."

"I would like SPSS to improve its integration with other data-filing IBM tools. I also think its duration with data, utilization, and graphics could be better."

"The technical support should be improved."

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

"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 solution needs to improve forecasting using time series analysis."

"Improvements are needed in the user interface, particularly in terms of user-friendliness."

More IBM SPSS Statistics cons

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

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

"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."

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

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

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

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

More SAS Analytics cons

Pricing and Cost Advice

"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."

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

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

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

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

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

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

More IBM SPSS Statistics pricing and cost advice

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

"Licensing was rather straightforward."

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

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

"Setup costs were quite reasonable."

"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."

More SAS Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

Manufacturing Company

University

Financial Services Firm

20%

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 Statistics?

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

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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 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

IBM SPSS Modeler vs IBM SPSS Statistics

Compared 25% of the time

TIBCO Statistica vs IBM SPSS Statistics

Compared 9% of the time

Weka vs IBM SPSS Statistics

Compared 9% of the time

Alteryx vs IBM SPSS Statistics

Compared 7% of the time

Microsoft Azure Machine Learning Studio vs IBM SPSS Statistics

Compared 4% of the time

More IBM SPSS Statistics Competitors

KNIME vs SAS Analytics

Compared 33% of the time

Oracle Advanced Analytics vs SAS Analytics

Compared 18% of the time

IBM SPSS Modeler vs SAS Analytics

Compared 15% of the time

Weka vs SAS Analytics

Compared 15% of the time

More SAS Analytics Competitors

Product Reports

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 Statistics

No data available

Overview

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

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

Buyer's Guide

IBM SPSS Statistics vs. SAS Analytics

June 2025

Free Report: IBM SPSS Statistics vs. SAS Analytics

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