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KNIME vs Weka comparison

 

Comparison Buyer's Guide

Executive Summary

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

KNIME
Ranking in Data Mining
1st
Average Rating
8.2
Reviews Sentiment
7.1
Number of Reviews
60
Ranking in other categories
Data Science Platforms (2nd)
Weka
Ranking in Data Mining
2nd
Average Rating
7.6
Reviews Sentiment
6.6
Number of Reviews
14
Ranking in other categories
Anomaly Detection Tools (4th)
 

Mindshare comparison

As of April 2025, in the Data Mining category, the mindshare of KNIME is 25.7%, down from 27.4% compared to the previous year. The mindshare of Weka is 20.3%, down from 20.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Mining
 

Featured Reviews

Laurence Moseley - PeerSpot reviewer
Has a drag-and-drop interface and AI capabilities
It's difficult to pinpoint one single feature because KNIME has so many. For starters, it's very easy to learn. You can get started with just a one-hour video. The drag-and-drop interface makes it user-friendly. For example, if you want to read an Excel file, drag the "read Excel file" node from the repository, configure it by specifying the file location, and run it. This gives you a table with all your data. Next, you can clean the data by handling missing values, selecting specific columns you want to analyze, and then proceeding with your analysis, such as regression or correlation. KNIME has over 4,500 nodes available for download. In addition, KNIME offers various extensions. For instance, the text processing extension allows you to process text data efficiently. It's more powerful than other tools like NVivo and Palantir. KNIME also has AI capabilities. If you're unsure about the next step, the AI assistant can suggest the most frequently used nodes based on your previous work. Another valuable feature is the integration with Python. If you need to perform a task that requires Python, you can simply add a Python node, write the necessary code,
AwaisAnwar - PeerSpot reviewer
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.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The solution allows for sharing model designs and model operations with other data analysts."
"It's a very powerful and simple tool to use."
"KNIME is very easy to handle and use. Anyone can use it, and it's easy to learn."
"I know I don't use it to its full capacity, but I love the Rule Engine feature. It has allowed me to create lookup tables on the fly and break down text fields into quantifiable data."
"The most valuable is the ability to seamlessly connect operators without the need for extensive programming."
"KNIME is more intuitive and easier to use, which is the principal advantage."
"It is a stable solution...It is a scalable solution."
"I would rate the stability of KNIME a ten out of ten."
"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."
"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."
"It is a stable product."
"It doesn’t cost anything to use the product."
"The interface is very good, and the algorithms are the very best."
"I mainly use this solution for the regression tree, and for its association rules. I run these two methodologies for Weka."
"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."
"In Weka, anyone can access the program without being a programmer, which is a good feature since the entry cost is very low."
 

Cons

"From the point of view of the interface, they can do a little bit better."
"Not just for KNIME, but generally for software and analyzing data, I would welcome facilities for analyzing different sorts of scale data like Likert scales, Thurstone scales, magnitude ratio scales, and Guttman scales, which I don't use myself."
"The dynamic column name feature could be improved. When attempting to automate processes involving columns, such as with companies, it becomes difficult to achieve the same result when we make changes."
"KNIME could improve when it comes to large data markets."
"The solution is inconvenient when it comes to wrangling data that includes multiple steps or features because each step or feature requires its own icon."
"The predefined workflows could use a bit of improvement."
"When deploying models on a regular system, it works fine. However, when accuracy is a priority, hyperparameter tuning is necessary. Currently, KNIME doesn't have the best tools for this which they could improve in this area."
"The visualization functionalities are not good (cannot be compared to, for instance, the possibilities in R)."
"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."
"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."
"Not particularly user friendly."
"Weka could be more stable."
"In terms of scalability, I think Weka is not prepared to handle a large number of users."
"If there are a lot more lines of code, then we should use another language."
"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."
"Weka is a little complicated and not necessarily suited for users who aren't skilled and experienced in data science."
 

Pricing and Cost Advice

"KNIME is a cheap product. I currently use KNIME's open-source version."
"KNIME assets are stand alone, as the solution is open source."
"Scaling to the on-premises version requires a licensing fee per user that is a bit expensive in comparison to R, Python, and SAS."
"While there are certain limitations in functionality, you can still utilize it efficiently free of charge."
"With KNIME, you can use the desktop version free of charge as much as you like. I've yet to hit its limits. If I did, I'd have to go to the server version, and for that you have to pay. Fortunately, I don't have to at the moment."
"It is free of cost. It is GNU licensed."
"KNIME is free and open source."
"For beginners, the free desktop version is very attractive, but the full server version can be more expensive. I have only used the free version and it offers a fair pricing system. I have been promoting it to others without any compensation or request from the company, simply because I am enthusiastic about it. I am not aware of the pricing for the server version, but it seems to be widely used."
"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."
"The solution is free and open-source."
"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
13%
Manufacturing Company
11%
Computer Software Company
9%
University
8%
University
19%
Educational Organization
15%
Computer Software Company
11%
Financial Services Firm
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about KNIME?
Since KNIME is a no-code platform, it is easy to work with.
What is your experience regarding pricing and costs for KNIME?
I rate the product’s pricing a seven out of ten, where one is cheap and ten is expensive.
What needs improvement with KNIME?
For graphics, the interface is a little confusing. So, this is a point that could be improved.
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?
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...
 

Comparisons

 

Also Known As

KNIME Analytics Platform
No data available
 

Overview

 

Sample Customers

Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
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Find out what your peers are saying about KNIME vs. Weka and other solutions. Updated: April 2025.
848,716 professionals have used our research since 2012.