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: November 2026).

IBM SPSS Modeler vs. Weka

November 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

5th

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Anomaly Detection Tools (1st)

Mindshare comparison

As of November 2026, in the Data Mining category, the mindshare of IBM SPSS Modeler is 13.3%, down from 21.4% compared to the previous year. The mindshare of Weka is 7.4%, down from 11.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining Mindshare Distribution
Product	Mindshare (%)
IBM SPSS Modeler	13.3%
Weka	7.4%
Other	79.3%

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

"So far, the stability has been rock solid."

"Some basic form of feature engineering for classification models. This really quickens the model development process."

"The supervised models are valuable. It is also very organized and easy to use."

"It’s definitely scalable, it’s all on the same platform, it’s well integrated. I think the integration is important in terms of scalablility because essentially, having the entire suite helps a lot to scale it"

"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."

"IBM SPSS Modeler is the easiest solution."

"IBM was chosen because of usability. It's point and click, whereas the other out-of-the box-solution, or open-source solutions, require full-on programming and a much higher skill level."

More IBM SPSS Modeler pros

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

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

"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."

"Weka is a very easy to use Data Mining solution, great for learning and for doing small experiments before exploring the data deeper, with a large number and diversity of algorithms that make it an excellent solution for rapid testing."

"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."

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

"Using Weka has positively impacted my studies and projects because it has saved my time firstly."

"The interface is very good, and the algorithms are the very best."

More Weka pros

Cons

"There are performance issues. Extracting data from many combined tables can take hours and occasionally crash the server due to memory leaks. This performance problem bothers people. The performance issue seems to be related to the server. We design streams on the client and submit them to the server, which generates a large SQL statement. There are two potential bottlenecks: one in the server and another in data extraction. I'm unsure about the exact mechanics of data splitting when fetching from the database."

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

"Setup is a little problematic for desktop. A nightmare for server."

"Easier coding language that is more flexible with other platforms."

"The product does not have a search function for tags."

"It would be helpful if SPSS supported open-source features, for example, embedding R or Python scripts in SPSS Modeler."

"The integration with sources and visualisation needs some improvement. The scalability needs improvement."

"It would be beneficial if the tool would include more well-known machine learning algorithms."

More IBM SPSS Modeler cons

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

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

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

"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."

"Help documentation could be more user friendly."

"Weka could be more stable."

"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."

"Documentation tends to lag and is sometimes inaccurate, but we have found that looking at the most recent version tends to show more accurate documents."

More Weka cons

Pricing and Cost Advice

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

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

"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."

"It is an expensive product."

"The scalability was kind of limited by our ability to get other people licenses, and that was usually more of a financial constraint. It's expensive, but it's a good tool."

"$5,000 annually."

"When you are close to end of quarter, IBM and its partners can get you 60% to 70% discounts, so literally wait for the last day of the quarter for the best prices. You may feel like you are getting robbed if you can't receive a good discount."

"It got us a good amount of money with quick and efficient modeling."

More IBM SPSS Modeler 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."

"The solution is free and open-source."

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

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Top Industries

By visitors reading reviews

Outsourcing Company

Financial Services Firm

Government

Construction Company

Educational Organization

15%

University

12%

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 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 advice do you have for others considering IBM SPSS Modeler?

You should put MATLAB into your database. According to Gartner, from what I have seen last year, there was a Gartner four quadrants perspective, and MATLAB was in a very good position. I remember a...

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...

IBM SPSS Statistics vs IBM SPSS Modeler

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Compared 8% of the time

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Product Reports

Download IBM SPSS Modeler product report

IBM SPSS Modeler

October 2026

Download Weka product report

October 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

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