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

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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

6.6

Number of Reviews

Ranking in other categories

Data Science Platforms (17th)

Weka

Ranking in Data Mining

2nd

Average Rating

7.6

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Anomaly Detection Tools (4th)

Mindshare comparison

As of July 2025, in the Data Mining category, the mindshare of IBM SPSS Modeler is 17.9%, up from 16.3% compared to the previous year. The mindshare of Weka is 17.7%, down from 21.1% 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 most valuable features of the IBM SPSS Modeler are visual programming, you don't have to write any code, and it is easy to use. 90 to 95 percent of the use cases, you don't have to fine-tune anything. If you want to do something deeper, for example, create a better neural network, then you have to go into the features and try to fine-tune them. However, the default selection which is made by the tool, it's very practical and works well."

"It scales. I have not run into any challenges where it will not perform."

"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."

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

"The ease of use in the user interface is the best part of it. The ability to customize some of my streams with R and Python has been very useful to me, I've automated a few things with that."

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

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

"We had an IBM Guardium service contract where we used one of their resources to help us develop our prototype. It was a good experience, but they were helpful and responsive."

More IBM SPSS Modeler pros

"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 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."

"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."

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

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

More Weka pros

Cons

"Unstructured data is not appropriate for SPSS Modeler."

"I would not rate the technical support very well. The technicians have accents. When you do find someone, it is very hard to get somebody able to answer the technical questions."

"I think mapping for geographic data would also be a really great thing to be able to use."

"It is very good, but slow. The slowness may be because we have not finalized all the background information in SPSS. It still needs some tweaking."

"The forecasting could be a bit easier."

"It would be good if IBM added help resources to the interface."

"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."

"Customer support is hard to contact."

More IBM SPSS Modeler cons

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

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

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

"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."

"Weka could be more stable."

"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."

"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."

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

More Weka cons

Pricing and Cost Advice

"It is an expensive product."

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

"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."

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

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

"It is a huge increase to time savings."

"$5,000 annually."

"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."

More IBM SPSS Modeler pricing and cost advice

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

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

11%

Educational Organization

11%

Government

10%

University

18%

Educational Organization

17%

Computer Software Company

10%

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

IBM SPSS Modeler

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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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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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IBM SPSS Modeler vs. Weka