SAS Enterprise Miner vs Weka comparison

SAS and Weka are both solutions in the Data Mining category. SAS is ranked #7, while Weka is ranked #4. SAS holds a 4.8% mindshare in DM, compared to Weka’s 9.3% mindshare. Additionally, 93% of SAS users are willing to recommend the solution, compared to 78% of Weka users who would recommend it.

SAS Enterprise Miner

Read 13 SAS Enterprise Miner reviews

1,187 Views
392 Comparison Views

93% willing to recommend

Weka

Read 14 Weka reviews

1,550 Views
1,364 Comparison Views

78% willing to recommend

SAS Enterprise Miner

Weka

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Executive SummaryUpdated on May 21, 2025

SAS Enterprise Miner and Weka are competing data analysis tools within the analytics domain. While SAS Enterprise Miner is noted for its advanced analytical capabilities and structured support, Weka's flexibility and cost-effectiveness make it appealing to a broader audience.

Features: SAS Enterprise Miner provides comprehensive data mining capabilities such as predictive modeling, decision tree creation, and robust analytics integration within Base SAS. It handles large data sets efficiently and allows for customization using SAS code. Weka offers diverse machine learning algorithms, ease of use without programming, and integrates easily with Java for rapid testing and flexible applications.

Room for Improvement: SAS Enterprise Miner could improve its user interface and simplify its deployment process. Enhancing the visualization capabilities would make the tool more accessible for novice users. Weka would benefit from developing enhanced visualization features, expanding its enterprise-level functionalities, and offering more structured customer service to improve user experience.

Ease of Deployment and Customer Service: SAS Enterprise Miner involves a complex deployment process and requires a significant learning curve, but it is supported by extensive customer service. Weka boasts easier installation due to its open-source nature and has community-driven support, but lacks dedicated support services, which might limit assistance available compared to SAS.

Pricing and ROI: SAS Enterprise Miner demands a substantial initial investment due to its advanced features, offering higher ROI for large-scale operations. In contrast, Weka, being open-source, presents a much lower entry cost, attracting cost-conscious users seeking flexibility without the high financial commitment.

To learn more, read our detailed SAS Enterprise Miner vs. Weka Report (Updated: February 2026).

Buyer's Guide

SAS Enterprise Miner vs. Weka

February 2026

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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

SAS Enterprise Miner

Ranking in Data Mining

7th

Average Rating

7.6

Reviews Sentiment

6.2

Number of Reviews

Ranking in other categories

Data Science Platforms (24th)

Weka

Ranking in Data Mining

4th

Average Rating

7.6

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Anomaly Detection Tools (2nd)

Mindshare comparison

As of February 2026, in the Data Mining category, the mindshare of SAS Enterprise Miner is 4.8%, up from 4.4% compared to the previous year. The mindshare of Weka is 9.3%, down from 21.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining Market Share Distribution
Product	Market Share (%)
Weka	9.3%
SAS Enterprise Miner	4.8%
Other	85.9%

Data Mining

Featured Reviews

reviewer1352853

Executive Head of analytics at a retailer with 5,001-10,000 employees

A stable product that is easy to deploy and can be used for structured and unstructured data mining

We use the solution for predictive analytics to do structured and unstructured data mining I like the way the product visually shows the data pipeline. The product must provide better integration with cloud-native technologies. I have been using the solution for 20 years. The product is very…

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Xavier Suriol

Manager at XS AMSAFIS DATASETS, S.L.

A good solution offering a range of tools but is limited by its user-handling capacities

In a new machine learning job, if the method is a bit foreign to me, if I have to do it in R, it could be a tedious task. First, I need to identify the libraries required for the new methodology. This can involve identifying two, three, or even four libraries. Then, I need to read their manuals thoroughly. This is time-consuming. In Weka, as all machine learning tools are on my desktop, I easily find out the method. As a freelancer, people send me datasets, and I work on the statistics at home before providing the solution. When a solution needs to be implemented on a server, server programmers install it on the server. This is similar to Power BI, where I prepare files on my desktop, and someone else uploads them to the server for others to access. I think I cannot send a Weka solution to a server programmer. In Weka, anyone can run the program without being a programmer, which is a good feature since the entry cost is very low.

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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

"he solution is scalable."

"The technical support is very good."

"I like the way the product visually shows the data pipeline."

"Good data management and analytics."

"The most valuable feature is the decision tree creation."

"The setup is straightforward. Deployment doesn't take more than 30 minutes."

"The solution is able to handle quite large amounts of data beautifully."

"Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic."

More SAS Enterprise Miner pros

"It doesn’t cost anything to use the product."

"Weka is a very nice tool, it needs very small requirements. If I want to implement something in Python, I need a lot of memory and space but Weka is very lightweight. Anyone can implement any kind of algorithm, and we can show the results immediately to the client using the one-page feature. The client always wants to know the story. They want the result."

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

"I like the machine algorithm for clustering systems. Weka has larger capabilities. There are multiple algorithms that can be used for clustering. It depends upon the user requirements. For clustering, I've used DBSCAN, whereas for supervised learning, I've used AVM and RFT."

"Weka's best features are its user-friendly graphic interface interpretation of data sets and the ease of analyzing data."

"With clustering, if it's a yes, it's a yes, if it's a no, it's a no. It gives you a 100% level of accuracy of a model that has been trained, and that is in most cases, usually misleading. Classification is highly valuable when done as opposed to clustering."

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

"The path of machine learning in classification and clustering is useful. The GUI can get you results. No programming is needed. No need to write down your script first or send to your model or input your data."

More Weka pros

Cons

"Technical support could be improved."

"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."

"Virtualization could be much better."

"The initial setup is challenging if doing it for the first time."

"The ease of use can be improved. When you are new it seems a bit complex."

"The product must provide better integration with cloud-native technologies."

"The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch."

"The visualization of the models is not very attractive, so the graphics should be improved."

More SAS Enterprise Miner cons

"I believe is there are a few newer algorithms that are not present in the Weka libraries. Whereas, for example, if I want to have a solution that involves deep learning, so I don't think that Weka has that capability. So in that case I have to use Python for ... predict any algorithms based on deep learning."

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

"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."

"Not particularly user friendly."

"In terms of scalability, I think Weka is not prepared to handle a large number of users."

"The visualization of Weka is subpar and could improve. Machine learning and visualization do not work well together. For example, we want to know how we can we delete empty cells or how can we fill in the empty cells without cleaning the data system and putting it together."

"The filter section lacks some specific transformation tools. If you want to change a variable from a numeric variable to a categorical variable, you don't have a feature that can enable you to change a variable from a numeric variable to a categorical variable."

"While it might offer insights for basic warehouse tasks, it falls short of deeper understanding and results."

More Weka cons

Pricing and Cost Advice

"The solution is expensive for an individual, but for an enterprise/institution (purchasing bulk licenses), it is not a high price for the use that will come from it."

"The solution must improve its licensing models."

"This solution is for large corporations because not everybody can afford it."

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

21%

Educational Organization

11%

Manufacturing Company

10%

University

Educational Organization

16%

University

12%

Computer Software Company

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	4
Large Enterprise	7

By reviewers
Company Size	Count
Small Business	7
Midsize Enterprise	1
Large Enterprise	2

Comparisons

KNIME Business Hub vs SAS Enterprise Miner

Compared 14% of the time

Azure Data Lake Analytics vs SAS Enterprise Miner

Compared 12% of the time

Altair RapidMiner vs SAS Enterprise Miner

Compared 9% of the time

Databricks vs SAS Enterprise Miner

Compared 7% of the time

MathWorks Matlab vs SAS Enterprise Miner

Compared 6% of the time

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KNIME Business Hub vs Weka

Compared 34% of the time

IBM SPSS Statistics vs Weka

Compared 12% of the time

IBM SPSS Modeler vs Weka

Compared 12% of the time

DataRPM vs Weka

Compared 9% of the time

Oracle Advanced Analytics vs Weka

Compared 6% of the time

More Weka Competitors

Product Reports

Buyer's Guide

Data Mining

February 2026

Download SAS Enterprise Miner product report

Buyer's Guide

Weka

January 2026

Download Weka product report

Also Known As

Enterprise Miner

No data available

Overview

SAS Enterprise Miner is a solution to create accurate predictive and descriptive models on large volumes of data across different sources in the organization. SAS Enterprise Miner offers many features and functionalities for the business analysts to model their data. Some of the business applications are for detecting fraud, minimizing risk, resource demands, reducing asset downtime, campaigns and reduce customer attrition.

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.

Weka

Sample Customers

Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare

Information Not Available

Buyer's Guide

SAS Enterprise Miner vs. Weka

February 2026

Free Report: SAS Enterprise Miner vs. Weka

Find out what your peers are saying about SAS Enterprise Miner vs. Weka and other solutions. Updated: February 2026.

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