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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

"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."
"The Cloudera Data Science Workbench is customizable and easy to use."
"One of the greatest advantages of KNIME is that it can be used by those without any coding experience. those with no coding background can use it."
"It also has very good fundamental machine learning. It has decision trees, linear regression, and neural nets. It has a lot of text mining facilities as well. It's fairly fully-featured."
"The tool's analytic capabilities are good."
"It has allowed us to easily implement advanced analytics into various processes."
"Valuable features include visual workflow creation, workflow variables (parameterisation), automatic caching of all intermediate data sets in the workflow, scheduling with the server."
"Easy to connect with every database: We use queries from SQL, Redshift, Oracle."
"The product is open-source and therefore free to use."
"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."
 

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."
"I would like to see better web scraping because every time I tried, it was not up to par, although you can use Python script."
"The visualization functionalities are not good (cannot be compared to, for instance, the possibilities in R)."
"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."
"They should look at other vendors like Alteryx that are more user friendly and modern."
"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."
"There should be better documentation and the steps should be easier."
"Data visualization needs improvement."
"The pricing needs improvement."
 

Pricing and Cost Advice

"The product is expensive."
"KNIME is free as a stand-alone desktop-based platform but if you want to get a KNIME server then you can find the cost on their website."
"We're using the free academic license just locally. I went for KNIME because they have a free academic license."
"The price of KNIME is quite reasonable and the designer tool can be used free of charge."
"KNIME assets are stand alone, as the solution is open source."
"This is an open-source solution that is free to use."
"This is a free open-source solution."
"KNIME desktop is free, which is great for analytics teams. Server is well priced, depending on how much support is required."
"There is no cost for using KNIME because it is an open-source solution, but you have to pay if you need a server."
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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.