IBM Watson Explorer vs Weka comparison

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IBM Watson Explorer

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Executive Summary

We performed a comparison between IBM Watson Explorer and Weka based on real PeerSpot user reviews.

Find out in this report how the two Data Mining solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed IBM Watson Explorer vs. Weka Report (Updated: April 2025).

IBM Watson Explorer vs. Weka

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Helped 850,028 peers since 2012

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 Watson Explorer

Ranking in Data Mining

11th

Average Rating

8.4

Number of Reviews

Ranking in other categories

No ranking in other categories

Weka

Ranking in Data Mining

2nd

Average Rating

7.6

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

Anomaly Detection Tools (4th)

Mindshare comparison

As of May 2025, in the Data Mining category, the mindshare of IBM Watson Explorer is 1.0%, up from 0.9% compared to the previous year. The mindshare of Weka is 18.9%, down from 20.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining

Featured Reviews

it_user840897

Head of Commercialization at Woodside Energy

Ingests, retrieves information from a range of sources; enables dissecting questions in context and answering them

WEX is more a platform, I believe, than it is the application. I could talk about what I'm looking for in the application. We've done visualizations and we can do basic analysis with the system as it stands. Where we're looking to take it is implementing it into workflows, so the workers on the line can actually understand the risks that they're exposing themselves to and then address them on the fly. So that's fantastic. And then the final one is, it's not prediction, but maybe anticipation. So when people are put at risk, we'll be implementing solutions shortly that will help people anticipate the risks and the dangers they're exposing themselves to so they can control them.

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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

"We take natural language that was happening in our repositories and our application and then feed it to the Watson APIs. We receive JSON payloads as an API response to get cognitive feedback from the repository data."

"I have found the auto-generated document very useful as well as the main keywords that are highlighted, which are used for the search functionality within IBM Watson Explorer."

"The valuable feature of Watson Explorer for us is data entities, and to see the hidden insights from within unstructured data."

"Ease of use is pretty good as is the standardization of not actually having to have my own natural learning algorithms, just to use the Watson APIs."

"For me, as a user, the most valuable feature is the ability to ingest and then retrieve information from a range of separate sources; the ability to dissect questions in context and actually answer them."

"The ability to easily pull together lots of different pieces of information and drill down in a smarter way than has been possible with other analytics tools is key. Watson is all based on a set of AI and deep learning, machine-learning capabilities, and it is looking behind the scenes at some relationships that you likely would not have spotted on your own. It's pulling things together, categorizing some things, that are not something that you might have seen on your own."

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

"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."

"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."

"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."

"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."

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

More Weka pros

Cons

"Much of IBM operates this way, where they have sets of tools that are in the middleware space, and it becomes the customer's responsibility or the business partner's responsibility to develop full solutions that take advantage of that middleware. I think IBM's finding itself in that spot with Watson-related technologies as well, where the capabilities to do really interesting and useful things for customers is there, but somebody still has to build it. Is that going to be the customer? Are they going to be willing to take on that responsibility themselves"

"Small businesses will probably have a little harder time getting into it, just because of the amount of resources that they have available, both financial and time, but it really is a solution that should work for them."

"It is a little bit tricky to get used to the workflow of knowing how to train Watson, what can be provided, what can't be, how to provide it, how to import, export, and what it means every time you have to add a new dictionary"

"Stability is actually one of the areas that could use improvement. Setting it up is always tough. Setting Explorer requires experts, but also the underlying platform is not that stable. So it really needs a good expert to keep it running."

"It needs better language support, to include some other languages. Also, they should improve the user interface."

"I would say, give some kind of a community edition, a free edition. A lot of companies do, even Amazon gives you some kind of trial and error opportunities. If they could provide something like that, it would be good."

"The solution is expensive."

"More cognitive feedback would be good. The natural language analysis is great, the sentiment analyzers are great. But I would just like to see more... innovation done with the Watson platform."

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

"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."

"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."

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

"Not particularly user friendly."

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

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

"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."

More Weka cons

Pricing and Cost Advice

"The solution is expensive."

"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."

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

"The solution is free and open-source."

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Top Industries

By visitors reading reviews

Computer Software Company

17%

Educational Organization

15%

University

11%

Financial Services Firm

11%

University

19%

Educational Organization

15%

Computer Software Company

11%

Financial Services Firm

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

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What do you like most about Weka?

It is a stable product.

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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.

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What needs improvement with Weka?

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Comparisons

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KNIME vs Weka

Compared 61% of the time

IBM SPSS Statistics vs Weka

Compared 15% of the time

IBM SPSS Modeler vs Weka

Compared 8% of the time

Splunk User Behavior Analytics vs Weka

Compared 5% of the time

SAS Analytics vs Weka

Compared 4% of the time

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Product Reports

IBM Watson Explorer

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Also Known As

IBM WEX

No data available

Overview

IBM Watson Explorer is a cognitive exploration and content analysis platform that lets you listen to your data for advice. Explore and analyze structured, unstructured, internal, external and public content to uncover trends and patterns that improve decision-making, customer service and ROI. Leverage built-in cognitive capabilities powered by machine learning models, natural language processing and next-generation APIs to unlock hidden value in all your data. Gain a secure 360-degree view of customers, in context, to deliver better experiences for your clients.

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

RIMAC, Westpac New Zealand, Toyota Financial Services, Swiss Re, Akershus University Hospital, Korean Air Lines, Mizuho Bank, Honda

Information Not Available

IBM Watson Explorer vs. Weka