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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
24th
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
2nd
Average Rating
8.2
Reviews Sentiment
6.5
Number of Reviews
21
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of April 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 5.9%, down from 12.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Dataiku5.9%
Cloudera Data Science Workbench1.8%
Other92.3%
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

"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."
"The Cloudera Data Science Workbench is customizable and easy to use."
"Dataiku is highly regarded as it is a leader in the Gartner ranking."
"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 has positively impacted my organization, specifically in one project where we performed migration from AWS to Dataiku, speeding up the solution by close to 40% and reducing architecture costs by almost 70%, which was a significant benefit and greatly impacted our operations."
"I like the interface, which is probably my favorite part of the solution; it is really user-friendly, colorful, and I think it is really beautiful and well-designed."
"I rate the overall product as eight out of ten."
"Dataiku has positively impacted my organization as most of our projects have been migrated to Dataiku, and now people are relying on it as a go-to tool for all our data use cases."
"The advantage is that you can focus on machine learning while having access to what they call 'recipes.' These recipes allow me to preprocess and prepare data without writing any code."
"Traceability is vital since I manage many cohorts, and collaboration is key as I have multiple engineers substituting for one another."
 

Cons

"We found this solution a little bit difficult to scale."
"Running this solution requires a minimum of 12GB to 16GB of RAM."
"The tool's MLOps is not good. It's pricing also needs to improve."
"However, I feel that better documentation is necessary."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"I think it would help if Data Science Studio added some more features and improved the data model."
"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."
"There were stability issues: 1) SQL operations, such as partitioning, had bugs and showed wrong results. 2) Due to server downtime, scheduled processes used to fail. 3) Access to project folders was compromised (privacy issue) with wrong people getting access to confidential project folders."
"There were stability issues: 1) SQL operations, such as partitioning, had bugs and showed wrong results. 2) Due to server downtime, scheduled processes used to fail. 3) Access to project folders was compromised (privacy issue) with wrong people getting access to confidential project folders."
"In terms of enhancing collaboration within my team, I would not say Dataiku is the best one because it's so expensive."
"The interface for the web app can be a bit difficult. It needs to have better capabilities, at least for developers who like to code."
 

Pricing and Cost Advice

"The product is expensive."
"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."
"Pricing is pretty steep. Dataiku is also not that cheap."
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Top Industries

By visitors reading reviews
Financial Services Firm
33%
Healthcare Company
7%
Manufacturing Company
6%
Computer Software Company
6%
Financial Services Firm
18%
Manufacturing Company
9%
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?
The licenses are a bit high for companies that are still hesitating to get started with using Dataiku. For my personal projects, I used the thirty-day free trial. Regarding my company, I did not ha...
What needs improvement with Dataiku Data Science Studio?
I have no suggestions for improvements because it's all good; it just sometimes lags a lot, and I don't know if the server is full or what, but it sometimes takes a lot of time while loading and re...
What is your primary use case for Dataiku Data Science Studio?
My main use case for Dataiku involves ETL pipelines, mainly for data analysis, and I majorly use SQL queries for that. For ETL pipelines and data analysis, I had to create the output by combining a...
 

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.
886,858 professionals have used our research since 2012.