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Cloudera Data Science Workbench vs KNIME Business Hub comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Nov 2, 2025

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

Cloudera Data Science Workb...
Ranking in Data Science Platforms
22nd
Average Rating
7.0
Reviews Sentiment
6.9
Number of Reviews
2
Ranking in other categories
No ranking in other categories
KNIME Business Hub
Ranking in Data Science Platforms
3rd
Average Rating
8.2
Reviews Sentiment
7.1
Number of Reviews
60
Ranking in other categories
Data Mining (1st)
 

Mindshare comparison

As of January 2026, in the Data Science Platforms category, the mindshare of Cloudera Data Science Workbench is 1.6%, up from 1.4% compared to the previous year. The mindshare of KNIME Business Hub is 8.7%, down from 11.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Market Share Distribution
ProductMarket Share (%)
KNIME Business Hub8.7%
Cloudera Data Science Workbench1.6%
Other89.7%
Data Science Platforms
 

Featured Reviews

Ismail Peer - PeerSpot reviewer
Program Management Lead Advisor at Unionbank Philippines
Useful for data science modeling but improvement is needed in MLOps and pricing
If you don't configure CDSW well, then it might be not useful for you. Deploying the tool can vary in complexity, but most of the time, it's relatively simple and straightforward. Triggering a job from data to production is easy, as the platform automates the deployment process. However, ensuring optimal resource allocation is essential for smooth operations.
DG
BI Analyst at a photography company with 11-50 employees
Enables fast project development with efficient workflow modifications and promising features while offering modularity and reusability
KNIME is simple and allows for fast project development due to its reusability. I appreciate the ability to make improvements or modifications in existing workflows. Although I have not yet used the forecasting and customer profiling features, I find them promising. Another effective feature is the ability to use GET request objects to retrieve data from websites or APIs. This makes iterative steps easy to manage. It is more elastic and modern compared to SAP Data Services, allowing node creation and regrouping components or steps for reuse in different projects.

Quotes from Members

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

Pros

"The Cloudera Data Science Workbench is customizable and easy to use."
"I appreciate CDSW's ability to logically segregate environments, such as data, DR, and production, ensuring they don't interfere with each other. The deployment of machine learning is fast and easy to manage. Its API calls are also fast."
"This solution is easy to use and it can be used to create any kind of model."
"Key features include: very easy-to-use visual interface; Help functions and clear explanations of the functionalities and the used algorithms; Data Wrangling and data manipulation functionalities are certainly sufficient, as well as the looping possibilities which help you to automate parts of the analysis."
"KNIME is more intuitive and easier to use, which is the principal advantage."
"It provides very fast problem solving and I don't need to do much coding in it. I just drag and drop."
"We have been able to appreciate the considerable reduction in prototyping time."
"KNIME is very easy to handle and use. Anyone can use it, and it's easy to learn."
"It allows for a user-friendly approach where you can simply drag and drop elements to create your model, which is a convenient and effective idea."
"I've never had any problems with stability."
 

Cons

"The tool's MLOps is not good. It's pricing also needs to improve."
"Running this solution requires a minimum of 12GB to 16GB of RAM."
"To enhance accessibility and user-friendliness, there is a need for improvements in the interface and usability of deep learning and large-scale learning languages."
"I wish there were more video training resources for KNIME. The current videos are very short, and most learning is text-based. Longer training sessions would be helpful, especially for complex flowchart use cases. Webinars focusing on starting projects and analyzing data would also be beneficial."
"There are some parameters that I would like to have at a bigger scale. The upper limit of one node that tries to find spots or areas in photos was too small for us. It would need to be bigger."
"Both RapidMiner and KNIME should be made easier to use in the field of deep learning."
"The license is quite expensive for us."
"KNIME could improve when it comes to large data markets."
"The visualization functionalities are not good (cannot be compared to, for instance, the possibilities in R)."
"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."
 

Pricing and Cost Advice

"The product is expensive."
"It is expensive to procure the license."
"It is free of cost. It is GNU licensed."
"KNIME is a cost-effective solution because it’s free of cost."
"KNIME Business Hub is expensive for small companies."
"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."
"There is a Community Edition and paid versions available."
"KNIME is free and open source."
"KNIME assets are stand alone, as the solution is open source."
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Top Industries

By visitors reading reviews
Financial Services Firm
36%
Manufacturing Company
9%
Healthcare Company
7%
Computer Software Company
5%
Financial Services Firm
12%
University
9%
Manufacturing Company
9%
Educational Organization
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business20
Midsize Enterprise16
Large Enterprise29
 

Questions from the Community

What do you like most about Cloudera Data Science Workbench?
I appreciate CDSW's ability to logically segregate environments, such as data, DR, and production, ensuring they don't interfere with each other. The deployment of machine learning is fast and easy...
What needs improvement with Cloudera Data Science Workbench?
The tool's MLOps is not good. It's pricing also needs to improve.
What is your primary use case for Cloudera Data Science Workbench?
We have different use cases. Our banking use case uses machine learning to identify customer life events and recommend the best-suited card products. These machine-learning models are deployed in o...
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?
I have seen the potential to interact with Python, which is currently a bit limited. I am interested in the newer version, 5.4, when it becomes available. The machine learning and profileration asp...
 

Also Known As

CDSW
KNIME Analytics Platform
 

Overview

 

Sample Customers

IQVIA, Rush University Medical Center, Western Union
Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
Find out what your peers are saying about Cloudera Data Science Workbench vs. KNIME Business Hub and other solutions. Updated: December 2025.
881,082 professionals have used our research since 2012.