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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
8.0
Reviews Sentiment
7.1
Number of Reviews
59
Ranking in other categories
Data Science Platforms (2nd)
Weka
Ranking in Data Mining
2nd
Average Rating
7.6
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

"Stability is excellent. I would give it a nine out of ten."
"What I like most about KNIME is that it's user-friendly. It's a low-code, no-code tool, so students don't need coding knowledge. You can make use of different kinds of nodes. KNIME even has a good description of each node."
"It can handle an unlimited amount of data, which is the advantage of using Knime."
"It's very convenient to write your own algorithms in KNIME. You can write it in Java script or Python transcript."
"The product is user-friendly."
"The product is very easy to understand even for non-analytical stakeholders. Sometimes we provide them with KNIME workflows and teach them how to run it on their own machine."
"The solution is very easy to use"
"KNIME is easy to learn."
"Weka's best features are its user-friendly graphic interface interpretation of data sets and the ease of analyzing data."
"I mainly use this solution for the regression tree, and for its association rules. I run these two methodologies for Weka."
"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."
"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."
"In Weka, anyone can access the program without being a programmer, which is a good feature since the entry cost is very low."
"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."
"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."
"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."
 

Cons

"The graphic features of KNIME need improvement"
"KNIME is not good at visualization."
"Sometimes, we needed more space to handle larger operations, especially since our machines had limited space and memory due to Kubernetes clusters."
"KNIME could improve when it comes to large data markets."
"They could add more detailed examples of the functionality of every node, how it works and how we can use it, to make things easier at the beginning."
"In my environment, I need to access a lot of servers with different characteristics and access methods. Some of my servers have to be accessed using proxy which is not supported by KNIME, so I still need to create the middleware to supply the source of my KNIME configurations."
"The most difficult part of the solution revolves around its areas concerning machine learning and deep learning."
"There should be better documentation and the steps should be easier."
"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."
"Weka is a little complicated and not necessarily suited for users who aren't skilled and experienced in data science."
"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."
"In terms of scalability, I think Weka is not prepared to handle a large number of users."
"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 could be more stable."
 

Pricing and Cost Advice

"They have different versions, but I am using the open-source one."
"The client versions are mostly free, and we pay only for the KNIME server version. It's not a cheap solution."
"KNIME desktop is free, which is great for analytics teams. Server is well priced, depending on how much support is required."
"KNIME assets are stand alone, as the solution is open source."
"KNIME offers a free version"
"The price for Knime is okay."
"We're using the free academic license just locally. I went for KNIME because they have a free academic license."
"KNIME 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."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Manufacturing Company
11%
Computer Software Company
9%
University
7%
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: March 2025.
845,040 professionals have used our research since 2012.