IBM SPSS Modeler vs Weka comparison

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IBM SPSS Modeler

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Executive SummaryUpdated on May 21, 2025

IBM SPSS Modeler and Weka are both key players in the data analysis and machine learning sector. IBM SPSS Modeler stands out with its strong enterprise integration and support, whereas Weka is favored for its open-source accessibility and comprehensive algorithm library.

Features: IBM SPSS Modeler provides advanced predictive analytics, easy integration with enterprise systems, and strong visualization tools. Weka offers a wide array of machine learning algorithms, open-source access, and flexibility in algorithm implementation.

Room for Improvement: IBM SPSS Modeler could improve by enhancing open-source collaboration, reducing costs, and increasing algorithm diversity. Weka might benefit from richer visualization capabilities, professional customer support, and improved large-scale data handling.

Ease of Deployment and Customer Service: IBM SPSS Modeler offers professional deployment services with dedicated customer support, ideal for enterprise-level needs. Weka is straightforward to install with community-backed support, catering to users valuing self-reliance and flexibility.

Pricing and ROI: IBM SPSS Modeler has higher initial costs but potentially greater ROI for businesses demanding extensive analytics and enterprise features. Weka is cost-effective with zero-cost setup, attracting budget-conscious users and educational institutions focused on efficiency over high upfront investment.

To learn more, read our detailed IBM SPSS Modeler vs. Weka Report (Updated: September 2026).

IBM SPSS Modeler vs. Weka

September 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

IBM SPSS Modeler

Ranking in Data Mining

3rd

Average Rating

8.0

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

Data Science Platforms (13th)

Weka

Ranking in Data Mining

4th

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Anomaly Detection Tools (1st)

Mindshare comparison

As of September 2026, in the Data Mining category, the mindshare of IBM SPSS Modeler is 14.9%, down from 15.7% compared to the previous year. The mindshare of Weka is 7.2%, down from 15.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining Mindshare Distribution
Product	Mindshare (%)
IBM SPSS Modeler	14.9%
Weka	7.2%
Other	77.9%

Data Mining

Featured Reviews

Prof. Dr. Rudolf Bisping

Business Owner at SASS GmbH

Support and flexibility enable effective project initiation and meet customer needs but deployment requires enhancement

The customer comes to you and says they want to deploy it and make a production out of this, which is very difficult and expensive with IBM SPSS Modeler. With MATLAB, there is no problem. I have a solution, and then I convert my MATLAB solution to C programming language. This I can deploy, and I can check it, and it is MISRA compatible. It is very easy to deploy it, to go from MATLAB to C or C++, which is actually needed in the car industry. In the car industry, they want to have it in the hardware. You cannot put MATLAB or IBM SPSS Modeler in the hardware of a car, but with C, there is no problem with a microcontroller. They can shoot it into the microcontroller, and I can check it with Polyspace, and it is MISRA compatible, which is an industrial standard. There is nothing similar in IBM SPSS Modeler. I made solutions with IBM SPSS Modeler, and then the customer said they wanted to make a production out of it, and it was not possible. I stopped with IBM SPSS Modeler 18. It is now 18.6 from what I know at the moment. I do not believe that there is a possibility to design a graphic user interface with it. It is itself a graphic user interface, where you put all sorts of little icons into the display.

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Joseph Kaiser

Staff Infrastructure Engineer at a manufacturing company with 201-500 employees

High-speed shared storage has accelerated AI research workflows and supports massive job queues

The best features Weka offers are high speed, exceptional performance, and reliability. It is probably the best file system I have ever used. These features have helped my workflows and users by enabling us to train and perform inferencing of AI workflows of proteins against target diseases, which allows us to run jobs in approximately half the time that we would with slower storage. Weka is always available, incredibly reliable, and backed up, so we could not do this work without it. Additionally, Weka is incredibly easy to use because there is a web UI that allows us to create and resize file systems at will, making different directory structures available to different users at any given time, and the speed is exceptional. Weka has positively impacted my organization because we previously had NFS, which would take down the cluster when under high load. Now we have no concerns about highly loaded multiple thousands of jobs running simultaneously against this file system. The system handles it without any issues. To share more about the scale, we have anywhere between 1,000 to 10,000 jobs in the queue at any given time, and the system handles it without any problems. Our volumes are approximately half a petabyte on one system and about a third of a petabyte on another system for various storage uses, and it enables all our work to go efficiently.

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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

"It is pretty scalable."

"It's a very good and reasonably priced solution."

"We have been able to do some predictive modeling with it"

"I used it mostly for the PCA, the principal component analysis, and I have been using that for my bachelor's thesis."

"GUI and flow management."

"It continues to be a very flexible platform, so that it handles R and Python and other types of technology. It seems to be growing with additional open-source movement out there on different platforms."

"It's a very organized product. It's easy to use."

"IBM SPSS Modeler is the easiest solution."

More IBM SPSS Modeler 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."

"The best features Weka offers are high speed, exceptional performance, and reliability, and it is probably the best file system I have ever used."

"Weka eliminates the need for coding, allowing you to easily set parameters and complete the majority of the machine learning task with just a few clicks."

"I think Weka is definitely a good investment, that is why we still use it."

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

"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 is very easy to use, is very complete, and provides many benefits to the end user."

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

More Weka pros

Cons

"The time series is a very important issue, however, it is not given its value in the package as it should be."

"C&DS will not meet our scalability needs."

"The platform that you can deploy it on needs improvement because I think it is Windows only. I do not think it can run off a Red Hat, like the server products. I am pretty sure it is Windows and AIX only."

"The biggest issue with the visual modeling capability is that we can't extract the SQL code under the hood."

"The forecasting could be a bit easier."

"When I do clustering, I want to try a different stream, but currently the only thing that I can really pick is averaging."

"When I used it in the office, back in the day, we did have some stability issues. Sometimes it just randomly crashed and we couldn't get good feedback. But when I use it for my own stuff now I don't have any problems."

"The standard package (personal) is not supported for database connection."

More IBM SPSS Modeler cons

"The solution doesn’t really have very good technical support."

"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."

"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."

"I'm not sure if it's reliable. It's a little difficult to get results, especially if you are on some other programs like Tableau."

"Not particularly user friendly."

"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. It's really very complicated."

"Help documentation could be more user friendly."

More Weka cons

Pricing and Cost Advice

"The government has funds and a budget, it's hard to say if it's expensive or cheap. In Canada, they have a yearly budget. They used to encourage people to use the modeler for development. If ten users use the server with ten licenses, it runs faster. But if forty users use the same appliance, everything slows down. People then think it's not easy to do things and prefer using remote tools like Python to extract data from the database. It's not about being expensive or cheap, but about people's knowledge and experience in how to do the work."

"It is a huge increase to time savings."

"It is an expensive product."

"This tool, being an IBM product, is pretty expensive."

"Its price is okay for a company, but for personal use, it is considered somewhat expensive."

"I am using the free version of IBM SPSS Modeler, it is the educational edition version."

"If you are in a university and the license is free then you can use the tool without any charges, which is good."

"Having in mind all four tools from Garner’s top quadrant, the pricing of this tool is competitive and it reflects the quality that it offers."

More IBM SPSS Modeler pricing and cost advice

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

"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."

"The solution is free and open-source."

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

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Top Industries

By visitors reading reviews

Outsourcing Company

Financial Services Firm

Government

Construction Company

Educational Organization

15%

University

13%

Comms Service Provider

Construction Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	9
Midsize Enterprise	4
Large Enterprise	32

By reviewers
Company Size	Count
Small Business	11
Midsize Enterprise	2
Large Enterprise	5

Questions from the Community

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

The government has funds and a budget, it's hard to say if it's expensive or cheap. In Canada, they have a yearly budget. They used to encourage people to use the modeler for development. If ten us...

What needs improvement with IBM SPSS Modeler?

What is your primary use case for IBM SPSS Modeler?

I have been using IBM SPSS Modeler for a long time. I am using IBM SPSS Modeler mainly for ETL. Sometimes I use it to compare the results of the modeling as compared to MATLAB. MATLAB is the main t...

What is your experience regarding pricing and costs for Weka?

My experience with pricing, setup cost, and licensing has been that we have received very good terms, and the setup cost and licensing have been easy to implement, with pricing exactly what we woul...

What needs improvement with Weka?

Weka can be improved in terms of not having to reboot nodes when operator versions need to be changed, but they are working toward that. Documentation tends to lag and is sometimes inaccurate, but ...

What is your primary use case for Weka?

My main use case for Weka is providing a high-speed shared file system on converged infrastructure. A specific example of how I use Weka for this shared file system is that we host user home direct...

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Product Reports

Download IBM SPSS Modeler product report

IBM SPSS Modeler

September 2026

Download Weka product report

August 2026

Also Known As

SPSS Modeler

No data available

Overview

IBM SPSS Modeler is a robust tool that facilitates predictive modeling and data analysis through intuitive visual programming and customizable automation, enabling users to streamline data analytics processes with effectiveness.

IBM SPSS Modeler combines ease of use with powerful functionalities, including statistical analysis and quick prototyping. Users can leverage visual programming and drag-and-drop features, making data exploration efficient. Its diverse algorithms and capability to handle large datasets enable comprehensive data cleansing and predictive modeling. Integrating smoothly with Python enhances its versatility. However, improvements in machine learning algorithms, platform compatibility, and visualization tools are necessary. Licensing costs and existing performance issues may require consideration, particularly concerning data extraction and interface convenience.

What are the critical features of IBM SPSS Modeler?

Ease of Use: Features intuitive visual programming, facilitating smooth operation.
Customizable Automation: Supports personalized automation processes.
Visual Programming: Employs drag-and-drop interfaces for efficient task execution.
Integration with Python: Enhances flexibility with Python compatibility.
Diverse Algorithms: Supports a wide range of algorithms for data analysis.
Data Cleansing and Modeling: Enables rigorous data cleansing and predictive modeling.

What benefits or ROI should users consider?

Enhanced Productivity: Streamlined processes improve efficiency.
Flexible Integration: Accommodates R and Python, boosting adaptability.
Scalable Analytics: Capably handles large datasets and complex models.
Quick Prototyping: Facilitates rapid model development.
Improved Insights: Delivers profound analytical insights for decision-making.

IBM SPSS Modeler is implemented across various industries for diverse applications, including data analytics, predictive modeling, and HR analytics. Organizations utilize it to build models for customer segmentation and predictive analysis, leveraging its capabilities for large datasets, research, and educational purposes. It integrates efficiently with cloud and on-premise solutions, enhancing business analytics applications.

IBM

Weka provides a user-friendly platform for data processing and classification with a no-code interface, visual tools, and diverse algorithms. Its robust GUI supports seamless enterprise data integration and efficient performance on large datasets.

Weka is known for its simplicity and comprehensive algorithm selection, making it a popular choice for data exploration, processing, clustering, and mining. The platform is user-friendly and caters to both beginners and advanced users, supporting machine learning algorithms like classification, J48, KNN, regression, and clustering. Users leverage Weka for anomaly detection, data cleansing, and visualization, often in research and educational settings. Despite its strengths, users seek better Python integration and enhanced deep learning support, as well as improvements in data visualization, installation, and scalable solutions for big data scenarios.

What key features does Weka offer?

Simplicity: Intuitive design with a no-code interface for rapid project execution
Visualization: Comprehensive tools to assist in data interpretation and decision-making
Algorithm Variety: Wide range of options for data processing and classification
Performance: Efficient handling of large datasets with seamless enterprise integration
User-Friendliness: Robust GUI that assists both beginners and experienced users

What benefits and ROI do users see?

Time-Saving: Quick deployment with intuitive interfaces reduces project timelines
Flexibility: Adaptable to both on-premise and cloud-based deployment environments
Comprehensive Mining: Extensive capabilities allow for exhaustive data exploration
Ease of Use: Design caters to a range of users, enhancing accessibility and productivity

Weka is used across industries for projects involving data exploration and machine learning, enhancing research and educational initiatives. It transforms decision trees and neural networks, catering to diverse deployment requirements.

Sample Customers

Reisebªro Idealtours GmbH, MedeAnalytics, Afni, Israel Electric Corporation, Nedbank Ltd., DigitalGlobe, Vodafone Hungary, Aegon Hungary, Bureau Veritas, Brammer Group, Florida Department of Juvenile Justice, InSites Consulting, Fortis Turkey

Information Not Available