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Cloudera Data Science Workbench vs Dataiku comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

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
23rd
Average Rating
7.0
Reviews Sentiment
6.9
Number of Reviews
2
Ranking in other categories
No ranking in other categories
Dataiku
Ranking in Data Science Platforms
4th
Average Rating
8.2
Reviews Sentiment
6.5
Number of Reviews
20
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of March 2026, in the Data Science Platforms category, the mindshare of Cloudera Data Science Workbench is 1.8%, up from 1.3% compared to the previous year. The mindshare of Dataiku is 6.7%, down from 12.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Dataiku6.7%
Cloudera Data Science Workbench1.8%
Other91.5%
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.
SK
Senior Data Scientist at Deloitte
Visual workflows have streamlined healthcare analytics and have reduced reporting time significantly
In terms of improvement, I cannot comment on the LLMs or the agentic view as I have not used them yet. However, I feel that better documentation is necessary. Dataiku should establish a stronger community since this is proprietary software, where users can share knowledge. Although they have some community interaction, it is often challenging to find assistance when stuck. For example, when I was new to Dataiku and trying to use an external optimization tool such as CPLEX, I struggled with resource directory linking to a project's notebook. Detailed documentation and community discussions could have significantly alleviated these issues for users such as myself.

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."
"The most valuable feature is the set of visual data preparation tools."
"Dataiku is highly regarded as it is a leader in the Gartner ranking."
"I consider the return on investment with Dataiku valuable because for us, it is one single platform where all our data scientists come together and work on any model building, so it is collaboration, plus having everything in one place, organized, having proper project management, and then built-in capabilities which help to facilitate model building."
"The best features Dataiku offers include the ability for users to use the node without having to code and the functionality related to low-code/no-code."
"The most valuable feature of this solution is that it is one tool that can do everything, and you have the ability to very easily push your design to prediction."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"Dataiku has positively impacted my organization since we use it majorly for our day-to-day work, and it is very helpful in creating and managing ETL pipelines to create a project flow, making it easy to go back to any step and then make edits if some changes occur."
"Dataiku is really a very intuitive platform that allows you to carry out data projects from end to end, with the opportunity to reuse templates, models, and recipes, which is one of the big advantages of using it."
 

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."
"The license is very expensive. It would be great to have an intermediate license for basic treatments that do not require extensive experience."
"In the next release of this solution, I would like to see deep learning better integrated into the tool and not simply an extension or plugin."
"We still encounter some integration issues."
"The license is very expensive."
"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"Dataiku's scalability is not one of the best solutions to scale."
"However, I feel that better documentation is necessary."
"I have not seen a return on investment with Dataiku in terms of time saved, money saved, or fewer employees needed."
 

Pricing and Cost Advice

"The product is expensive."
"Pricing is pretty steep. Dataiku is also not that cheap."
"The annual licensing fees are approximately €20 ($22 USD) per key for the basic version and €40 ($44 USD) per key for the version with everything."
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Top Industries

By visitors reading reviews
Financial Services Firm
35%
Manufacturing Company
9%
Healthcare Company
7%
Computer Software Company
5%
Financial Services Firm
18%
Manufacturing Company
10%
Computer Software Company
9%
Energy/Utilities Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business6
Midsize Enterprise2
Large Enterprise13
 

Questions from the Community

Ask a question
Earn 20 points
What is your experience regarding pricing and costs for Dataiku Data Science Studio?
I am not the person involved in the process regarding pricing, setup cost, and licensing.
What needs improvement with Dataiku Data Science Studio?
To improve Dataiku, it could enhance its visualization features, as it is not possible in Dataiku to create direct visualizations or to integrate a web app directly or in a simpler way as it is pos...
What is your primary use case for Dataiku Data Science Studio?
My main use case for Dataiku is for data science and AI projects. I use Dataiku for a demand forecasting use case where the objective is to predict the demand for each product for the next four mon...
 

Also Known As

CDSW
Dataiku DSS
 

Overview

 

Sample Customers

IQVIA, Rush University Medical Center, Western Union
BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
Find out what your peers are saying about Cloudera Data Science Workbench vs. Dataiku and other solutions. Updated: March 2026.
884,873 professionals have used our research since 2012.