IBM SPSS Statistics vs SAS Analytics comparison

IBM and SAS are both solutions in the Data Mining category. IBM is ranked #2 with an average rating of 9.0, while SAS is ranked #5 with an average rating of 8.7. IBM holds a 17.2% mindshare in DM, compared to SAS’s 7.8% mindshare. Additionally, 89% of IBM users are willing to recommend the solution, compared to 95% of SAS users who would recommend it.

IBM SPSS Statistics

Read 40 IBM SPSS Statistics reviews

4,071 Views
1,669 Comparison Views

89% willing to recommend

SAS Analytics

Read 13 SAS Analytics reviews

1,073 Views
1,062 Comparison Views

95% willing to recommend

IBM SPSS Statistics

SAS Analytics

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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: April 2026).

Buyer's Guide

IBM SPSS Statistics vs. SAS Analytics

April 2026

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Helped 886,976 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 Statistics

Ranking in Data Mining

2nd

Average Rating

8.2

Reviews Sentiment

6.4

Number of Reviews

Ranking in other categories

Data Science Platforms (12th), AI Data Analysis (17th), AI Research (4th)

SAS Analytics

Ranking in Data Mining

5th

Average Rating

9.2

Reviews Sentiment

5.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of April 2026, in the Data Mining category, the mindshare of IBM SPSS Statistics is 17.2%, up from 16.6% compared to the previous year. The mindshare of SAS Analytics is 7.8%, up from 6.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining Mindshare Distribution
Product	Mindshare (%)
IBM SPSS Statistics	17.2%
SAS Analytics	7.8%
Other	75.0%

Data Mining

Featured Reviews

EzzAbdelfattah

Associate Professor Of Statistics at a university with 10,001+ employees

Advanced predictive analytics have supported my research and student projects across many methods

The only function I may need to be added or hope to be added to IBM SPSS Statistics is how to treat unstructured data. This mainly exists with IBM SPSS Modeler, but I do not think it is able to treat something like videos and similar content unless you are using languages like Python inside IBM SPSS Modeler or inside IBM SPSS Statistics. For the menu itself, for the selection, it does not exist. Thinking of the future, I believe that the owners of IBM SPSS Statistics should think about improving the package itself to be able to treat unstructured data.

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Sm Chetish Makam

Student at Rit

Data management has become faster and clearer but integration and large data handling still need work

SAS Analytics needs to improve for entry-level people in my college because buying licenses is somewhat costly for small businesses. SAS Analytics is also somewhat complex for students who are entering the data field. Additionally, SAS Analytics is not good at integration with other environments, so it should improve on that, and some syntaxes are not good. SAS Analytics has an older architecture in some areas, so it should enhance the UX side and performance in some aspects. SAS Analytics documentation should improve to be clearer for students who are currently using or trying to use SAS Analytics, so the documentation should be simplified. Customer service is pretty good as of now, as they respond in two to four hours on business days, but faster response times may solve many problems and attract more users. I rate SAS Analytics seven or eight out of ten. SAS Analytics should improve in massive data handling, as I mentioned earlier. SAS Analytics struggles when it handles massive data, and it should also get top-tier support. The support should improve from two to four hours down to one hour or even thirty minutes. SAS Analytics should also offer more low-code options for those who do not know how to code or to save more time, and they should consider reducing their pricing. Currently, SAS Analytics has limited flexibility and very limited integration, so improvements in those areas are necessary. SAS Analytics student version does not handle long or lengthy data well right now, so it should improve on that point. As I have mentioned, it struggles with larger data sets, but for current small or medium data sets, it is very good. Customer support should improve to fifteen to thirty minutes or immediate live agents during business hours. The two to four hours wait can sometimes take more than one day, and that does not make sense. We have to stop all our work until they reply if we encounter critical problems, so they should improve for certain.

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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

"The solution is very comprehensive, especially compared to Minitabs, which is considered more for manufacturing. However, whatever data you want to analyze can be handled with SPSS."

"Who needs to spend thousands on a license for halfway decent software when R and Python work for free?"

"This product provides the opportunity to better explore data and provide complete data analysis because it works both with modeling and non-parametric analysis."

"In terms of the features I've found most valuable, I'd say the duration, the correlation, and of course the nonparametric statistics. I use it for reliability and survival analysis, time series, regression models in different solutions, and different types of solutions."

"Custom tables and macros: They allow us to create useful reports quickly for a broad audience."

"Since we are using the software as a statistical tool, I would say the best aspects of it are the regression and segmentation capabilities. That said, I've used it for all sorts of things."

"In comparison with other software, I found IBM SPSS Statistics to be the best one from my perspective."

"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

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

"SAS Analytics is a very versatile and comfortable tool and it is powerful because I can work with data from many millions of records, big data with SAS Analytics in a short time versus other software."

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

"It's a very good tool for typical data analytics and reporting, data management."

"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."

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

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

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

More SAS Analytics pros

Cons

"Most of the package will give you the fixed value, or the p-value, without an explanation as to whether it it significant or not. Some beginners might need not just the results, but also some explanation for them."

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

"The solution needs more planning tools and capabilities."

"The statistics should be more self-explanatory with detailed automated reports."

"This solution is not suitable for use with Big Data."

"I'm unsure if SPSS has a commercial offering for big servers, unlike KNIME, which does."

"I think the visualization and charting should be changed and made easier and more effective."

"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."

More IBM SPSS Statistics cons

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

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

"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."

"SAS Analytics struggles when it handles massive data, and it should also get top-tier support."

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

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

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

More SAS Analytics cons

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."

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

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

"More affordable training for new staff members."

"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."

"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

"Prices were comparable with alternative solutions."

"Licensing was rather straightforward."

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

"Setup costs were quite reasonable."

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

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

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

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

More SAS Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

19%

Manufacturing Company

Computer Software Company

University

Financial Services Firm

24%

University

13%

Computer Software Company

Outsourcing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	9
Midsize Enterprise	6
Large Enterprise	20

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	2
Large Enterprise	11

Questions from the Community

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

I think the price of the solution is very reasonable. The cost depends; you have the option for subscription or you can purchase the license. Most of our customers are paying every year for a type ...

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What needs improvement with IBM SPSS Statistics?

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What is your primary use case for IBM SPSS Statistics?

I do use IBM SPSS Statistics, and even my students are using it for their projects and reports while working on PhD or Master's degrees. They are analyzing data using it. In comparison with other s...

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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.

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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.

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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 33% of the time

Databricks vs IBM SPSS Statistics

Compared 6% of the time

KNIME Business Hub vs IBM SPSS Statistics

Compared 4% of the time

Altair RapidMiner vs IBM SPSS Statistics

Compared 3% of the time

IBM Watson Studio vs IBM SPSS Statistics

Compared 3% of the time

More IBM SPSS Statistics Competitors

KNIME Business Hub vs SAS Analytics

Compared 14% of the time

OpenText Intelligent Classification vs SAS Analytics

Compared 12% of the time

IBM SPSS Modeler vs SAS Analytics

Compared 12% of the time

Lytics Conductor vs SAS Analytics

Compared 11% of the time

SAS Enterprise Miner vs SAS Analytics

Compared 10% of the time

More SAS Analytics Competitors

Product Reports

Buyer's Guide

IBM SPSS Statistics

April 2026

Download IBM SPSS Statistics product report

Buyer's Guide

Data Mining

March 2026

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

April 2026

Free Report: IBM SPSS Statistics vs. SAS Analytics

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