SAS Analytics vs Weka comparison

Read 16 Weka reviews

1,574 Views
1,338 Comparison Views

81% willing to recommend

SAS Analytics

Comparison Buyer's Guide

Download the report

Executive SummaryUpdated on May 21, 2025

SAS Analytics and Weka are competing in data analysis and machine learning, each offering distinct advantages. SAS Analytics is preferred for its comprehensive analytical features, while Weka stands out for its ease of use and innovation in machine learning.

Features: SAS Analytics offers powerful statistical analysis, predictive analytics, and extensive data management tools. It is valued for its integration capabilities and robust reporting. Weka provides a wide array of machine learning algorithms, an intuitive interface for rapid experimentation, and easy model deployment, differentiating itself with a focus on user-friendliness and innovative solutions.

Room for Improvement: SAS could enhance its user interface to be more beginner-friendly and improve model deployment speed. Additionally, expanding community resources might enrich user engagement. Weka might benefit from better customer support depth, more robust data visualization tools, and enhanced scalability to accommodate larger enterprise-level data analyses.

Ease of Deployment and Customer Service: SAS Analytics ensures smooth deployment processes and comprehensive customer support known for its efficiency in resolving issues. Weka excels in straightforward deployment with accessible user platforms, albeit with community-driven support, which may be less comprehensive compared to SAS’s professional service approach.

Pricing and ROI: SAS Analytics involves higher initial costs justified by its robust toolset and support, promising significant ROI for large-scale enterprises. Weka, as an open-source solution, minimizes initial costs while offering high returns in suitable environments, with ROI depending largely on the users' technical skills. The cost and ROI dynamics distinctly set SAS and Weka apart, with SAS as the premium investment and Weka as a cost-effective alternative.

To learn more, read our detailed SAS Analytics vs. Weka Report (Updated: April 2026).

Download the complete report

SAS Analytics vs. Weka

April 2026

Helped 889,855 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

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

Weka

Ranking in Data Mining

4th

Average Rating

7.8

Reviews Sentiment

6.4

Number of Reviews

Ranking in other categories

Anomaly Detection Tools (1st)

Mindshare comparison

As of April 2026, in the Data Mining category, the mindshare of SAS Analytics is 7.8%, up from 6.1% compared to the previous year. The mindshare of Weka is 8.0%, down from 20.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining Mindshare Distribution
Product	Mindshare (%)
Weka	8.0%
SAS Analytics	7.8%
Other	84.2%

Data Mining

Featured Reviews

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.

Read full review

Sm Chetish Makam

Student at Rit

Data mining projects have become faster and visualization now guides our pattern discovery

Weka can be improved in some areas. As a one-year user, I can share my experiences. I have tried installing other packages into Weka using the inbuilt package manager or adding modern algorithms that I wish to apply to my data sets or data processing. I think Weka needs to improve in that and also in integrating Python into Weka, which would help users much more. I chose eight out of ten because we need improvements in Weka, such as installing inbuilt packages. Weka uses skips such as N+2 or N+4 and eight-node, which makes sense basically, but I think it should improve in the package attribute, such as configuring Python easily and adding modern algorithms into Weka more easily.

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

"They have provided virtually everything we have needed to accomplish our task, as well as continuously improving our accuracy."

"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."

"They have provided virtually everything we have needed to accomplish our task, as well as continuously improving our accuracy."

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

"I think that the cost-benefit ratio is okay, it is the right balance."

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

"The team immediately resolves the issues."

"It has facilitated timely analysis results with quality work, meaningful output, and consistent data use."

More SAS Analytics pros

"It’s pretty straightforward, it's user-friendly, it’s free, and with YouTube videos, online guides, and e-books on machine learning using Weka, you can quickly learn to use its good interface for data visualization, filtering, and creating different scenarios and instances."

"There are many options where you can fill all of the data pre-processing options that you can implement when you're importing the data. You can also normalize the data and standardize it in an easier way."

"Weka is a very nice tool and it helped me to solve any machine learning problem in one minute."

"My main recommendation is that if you want artificial intelligence, or machine learning, go for an easy and quick tool like Weka, otherwise, any language will have a more expensive entry cost."

"Working with complicated algorithms in huge datasets is really easy in Weka."

"In Weka, anyone can access the program without being a programmer, which is a good feature since the entry cost is very low."

"But Weka helped me with this analysis in an easy way."

"It is a stable product."

More Weka pros

Cons

"SAS Analytics could improve in areas such as handling stress tests and workloads, as well as predicting financial movements, specifically profit and loss movements."

"This solution should be made more user-friendly. It needs a better visual output to explain logic to senior executives."

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

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

"SAS is very expensive. The challenge with them is that you have to pay for a license with every module you buy."

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

"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."

More SAS Analytics cons

"The product is good, but I would like it to work with big data. I know it has a Spark integration they could use to do analysis in clusters, but it's not so clear how to use it."

"Weka is not horizontally scalable. If I had to run a large dataset over Weka I would have to have a very large usage."

"With Python and R, you can do anything — you have that confidence, but with Weka, I don't have that confidence."

"Weka could be more stable."

"If you have one missing value in your dataset and this missing value belongs to a specific attribute and the attribute is a numeric attribute and there is only one missing data, whenever you import this data, the problem is that Weka cannot understand that this is a numeric field; it converts everything into a string, and there is no way to convert the string into numerical math."

"If there are a lot more lines of code, then we should use another language."

"Help documentation could be more user friendly."

"A few people said it became slow after a while."

More Weka cons

Pricing and Cost Advice

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

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

"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."

"Prices were comparable with alternative solutions."

"SAS is very expensive."

"Setup costs were quite reasonable."

More SAS Analytics pricing and cost advice

"We use the free version now. My faculty is very small."

"As far as I know, Weka is a freeware tool, and I am not aware if they have an online solution or if it is a commercial product."

"Currently, I am using an open-source version so I don't know much about the price of this solution."

"The solution is free and open-source."

See which vendors are best for you

Use our free recommendation engine to learn which Data Mining solutions are best for your needs.

See recommendations

889,855 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

24%

University

13%

Computer Software Company

Outsourcing Company

Educational Organization

17%

University

15%

Comms Service Provider

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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

By reviewers
Company Size	Count
Small Business	11
Midsize Enterprise	1
Large Enterprise	3

Questions from the Community

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.

What needs improvement with SAS Analytics?

With SAS Analytics, I find that the graphs are very poor, and since I use Power BI, I think SAS Analytics needs to enhance the visualization options to do better visualizations. Many other software...

What is your primary use case for SAS Analytics?

I work with SAS Analytics solutions, specifically with SAS Data Mining, because I extract information from the core system of the bank via ODBC connections and use SAS Base on the servers. I am the...

What needs improvement with Weka?

I think Weka could improve by providing more analysis options, though I am uncertain about specific recommendations at this moment.

What is your primary use case for Weka?

I use Weka in my process, study, and sciences for research with my students. I have experience with Weka's Experiment feature, as I use all the tools available in Weka. I utilize Weka's Experiment ...

What advice do you have for others considering Weka?

I use the free version of Weka, and I do not know the cost of the professional version or the lite version. I can recommend Weka to other users. I give this review a rating of 10.

KNIME Business Hub vs SAS Analytics

Comparisons

Compared 15% of the time

OpenText Intelligent Classification vs SAS Analytics

Compared 12% of the time

IBM SPSS Statistics vs SAS Analytics

Compared 11% of the time

IBM SPSS Modeler vs SAS Analytics

Compared 11% of the time

IBM Watson Explorer vs SAS Analytics

Compared 5% of the time

More SAS Analytics Competitors

KNIME Business Hub vs Weka

Compared 25% of the time

IBM SPSS Statistics vs Weka

Compared 12% of the time

IBM SPSS Modeler vs Weka

Compared 11% of the time

DataRPM vs Weka

Compared 11% of the time

Oracle Advanced Analytics vs Weka

Compared 5% of the time

More Weka Competitors

Product Reports

Download SAS Analytics product report

Data Mining

March 2026

Download Weka product report

March 2026

Overview

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

Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.

Sample Customers

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

Information Not Available