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 8.8, while SAS is ranked #5 with an average rating of 9.0. IBM holds a 18.5% mindshare in DM, compared to SAS’s 7.4% mindshare. Additionally, 89% of IBM users are willing to recommend the solution, compared to 94% of SAS users who would recommend it.

IBM SPSS Statistics

Read 40 IBM SPSS Statistics reviews

3,441 Views
1,548 Comparison Views

89% willing to recommend

SAS Analytics

Read 11 SAS Analytics reviews

811 Views
811 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: February 2026).

Buyer's Guide

IBM SPSS Statistics vs. SAS Analytics

February 2026

Download the complete report

Helped 882,160 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 (9th), AI Data Analysis (14th), AI Research (2nd)

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 February 2026, in the Data Mining category, the mindshare of IBM SPSS Statistics is 18.5%, up from 16.4% compared to the previous year. The mindshare of SAS Analytics is 7.4%, up from 6.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining Market Share Distribution
Product	Market Share (%)
IBM SPSS Statistics	18.5%
SAS Analytics	7.4%
Other	74.1%

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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Ernesto Tapia

Finance Business Intelligence at Banco Santander Mexico SA Institucion de Banca

Automated workflows enhance productivity but could better handle stress tests

I use SAS Analytics in my work to analyze data, such as selecting credits for traditional securitization. Recently, I used SAS Analytics for the project roster from Santander, selecting and evaluating credits, and conducting historical research on the reception of contracts to issue securitization…

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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

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

"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 feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can into multidimensional setup space. It's the multidimensional space facility that is most useful."

"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."

"The most valuable features mainly include factor analysis, correlation analysis, and geographic analysis."

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

"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."

"You can find a complete algorithm in the solution and use it. You don't need to write your own algorithms for predictive analytics. That's the most valuable feature and the main one we use."

More IBM SPSS Statistics pros

"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."

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

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

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

"The technical support is okay."

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

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

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

More SAS Analytics pros

Cons

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

"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."

"Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance."

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

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

"The technical support should be improved."

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

"It could allow adding color to data models to make them easier to interpret."

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."

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

"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."

"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."

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

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

More SAS Analytics cons

Pricing and Cost Advice

"More affordable training for new staff members."

"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."

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

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

"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."

"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."

More IBM SPSS Statistics pricing and cost advice

"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."

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

"SAS is very expensive."

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

"Prices were comparable with alternative solutions."

"Licensing was rather straightforward."

More SAS Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Manufacturing Company

Computer Software Company

University

Financial Services Firm

24%

Computer Software Company

10%

University

Construction 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	9

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.

See all answers

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?

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...

See all answers

Comparisons

IBM SPSS Modeler vs IBM SPSS Statistics

Compared 43% of the time

Databricks vs IBM SPSS Statistics

Compared 5% of the time

KNIME Business Hub vs IBM SPSS Statistics

Compared 4% of the time

Anaconda Business vs IBM SPSS Statistics

Compared 4% of the time

Dataiku vs IBM SPSS Statistics

Compared 2% of the time

More IBM SPSS Statistics Competitors

KNIME Business Hub vs SAS Analytics

Compared 23% of the time

IBM SPSS Modeler vs SAS Analytics

Compared 13% of the time

Lytics Conductor vs SAS Analytics

Compared 11% of the time

OpenText Intelligent Classification vs SAS Analytics

Compared 8% of the time

Oracle Advanced Analytics vs SAS Analytics

Compared 8% of the time

More SAS Analytics Competitors

Product Reports

Buyer's Guide

IBM SPSS Statistics

January 2026

Download IBM SPSS Statistics product report

Buyer's Guide

Data Mining

January 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

February 2026

Free Report: IBM SPSS Statistics vs. SAS Analytics

Find out what your peers are saying about IBM SPSS Statistics vs. SAS Analytics and other solutions. Updated: February 2026.

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