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: July 2025).

IBM SPSS Modeler vs. Weka

July 2025

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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

4th

Average Rating

8.0

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

Data Science Platforms (19th)

Weka

Ranking in Data Mining

3rd

Average Rating

7.6

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Anomaly Detection Tools (4th)

Mindshare comparison

As of August 2025, in the Data Mining category, the mindshare of IBM SPSS Modeler is 17.9%, up from 16.5% compared to the previous year. The mindshare of Weka is 17.8%, down from 20.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining

Featured Reviews

PeterHuo

Application Architect at Canada Border Services Agency

Good tool for extracting data from data warehouses, creating streams, and manipulating logic to extract final data

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. When streams become larger, performance bottlenecks may occur in the IBM SPSS Modeler server or the database. Sometimes the server crashes and needs to be restarted to release memory on both sides. I'm not sure exactly where the problem is caused, as I focus on stream design rather than server issues. The problem could be on the IBM SPSS Modeler server and database.

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AwaisAnwar

Treasury Management in Finance Department at National University of Pakistan

Open source, good for basic data mining use cases except for the visualization results

I haven't found it particularly useful. It lacks state-of-the-art algorithms and impressive outcomes. While it might offer insights for basic warehouse tasks, it falls short of deeper understanding and results. Moreover, a new user interface would be great, especially for beginners. Something that guides them through the available tools and helps them achieve their goals. I haven't seen anything like that myself, though maybe it's there and I missed it.

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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

"The visual modeling capability is one of its attractive features."

"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."

"It gives you a GUI interface, which is a lot more user-friendly and easier to use compared to writing R scripts or Python."

"You take two quarters and compare them and this tool is ideal because it gives you a lot of visibility on the before and after."

"We use analytics with the visual modeling capability to leverage productivity improvements."

"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"

"It handles large data better than the previous system that we were using, which was basically Excel and Access. We serve upwards of 300,000 parts over a 150 regions and we need to crunch a lot of numbers."

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

More IBM SPSS Modeler pros

"It is a stable product."

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

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

"I mainly use this solution for the regression tree, and for its association rules. I run these two methodologies for Weka."

"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."

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

"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 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

"We have run into a few problems doing some entity matching/analytics."

"If IBM could add some of the popular models into the SPSS for further analysis, like popular regression models, I think that would be a helpful improvement."

"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 time series should be improved."

"Formula writing is not straightforward for an Excel user. Totally new set of functions, which takes time to learn and teach."

"Requires more development."

"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."

"I understand that it takes some time to incorporate some of the new algorithms that have come out in the last few months, in the literature. For example, there is an algorithm based on how ants search for food. And there are some algorithms that have now been developed to complement rules. So that's one of the things that we need to have incorporated into it."

More IBM SPSS Modeler cons

"Not particularly user friendly."

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

"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."

"Within the basic Weka tool, I don't see many tools that are available where we can analyze and visualize the data that well."

"Weka is a little complicated and not necessarily suited for users who aren't skilled and experienced in data science."

"Weka could be more stable."

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

"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."

More Weka cons

Pricing and Cost Advice

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

"$5,000 annually."

"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."

"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."

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

"It is an expensive product."

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

"It is a huge increase to time savings."

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."

"The solution is free and open-source."

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

12%

Educational Organization

11%

Government

10%

University

18%

Educational Organization

17%

Computer Software Company

11%

Financial Services Firm

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about IBM SPSS Modeler?

Compared to other tools, the product works much easier to analyze data without coding.

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 do you like most about Weka?

It is a stable product.

What is your experience regarding pricing and costs for Weka?

Weka is free and open-source software. That is why I used it over KNIME.

What needs improvement with Weka?

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Product Reports

Download IBM SPSS Modeler product report

IBM SPSS Modeler

August 2025

Download Weka product report

July 2025

Also Known As

SPSS Modeler

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Overview

IBM SPSS Modeler is an extensive predictive analytics platform that is designed to bring predictive intelligence to decisions made by individuals, groups, systems and the enterprise. By providing a range of advanced algorithms and techniques that include text analytics, entity analytics, decision management and optimization, SPSS Modeler can help you consistently make the right decisions from the desktop or within operational systems.

Buy
https://www.ibm.com/products/spss-modeler/pricing

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https://www.ibm.com/account/reg/us-en/signup?formid=urx-19947

IBM

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

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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