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Dataiku vs Domino Data Science Platform 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

Dataiku
Ranking in Data Science Platforms
4th
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
17
Ranking in other categories
No ranking in other categories
Domino Data Science Platform
Ranking in Data Science Platforms
16th
Average Rating
7.6
Reviews Sentiment
6.7
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of January 2026, in the Data Science Platforms category, the mindshare of Dataiku is 8.0%, down from 12.1% compared to the previous year. The mindshare of Domino Data Science Platform is 2.3%, down from 2.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Market Share Distribution
ProductMarket Share (%)
Dataiku8.0%
Domino Data Science Platform2.3%
Other89.7%
Data Science Platforms
 

Featured Reviews

PriyankaSharma3 - PeerSpot reviewer
Cdao/Global Head Of Data And Analytics at Givaudan Roure
Unified platform has accelerated model development and improved collaborative data science work
I think Dataiku could be improved or enhanced in future releases with more 'talk to my data' capabilities, maybe more NLP features, and maybe a platform to build agents. These improvements would benefit me and my processes because they will help us to continue using Dataiku as one platform; right now we are exploring other platforms for the features which are missing, and if they are available within the same platform, I think it will increase the usage of Dataiku further. I think the pricing and licensing of Dataiku is a bit expensive; it could be improved further, and I think they should have a different kind of licensing model as well.
AS
Machine Learning Engineer at Unemployed
Accelerated machine learning model development with seamless deployment
We used Domino Data Science Platform for developing and working with machine learning models. It facilitated end-to-end development processes. Domino is based on Git, enabling collaboration similar to using Git. Each user operates on their own equivalent of a branch or fork, and once finished, they…

Quotes from Members

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

Pros

"Dataiku is highly regarded as it is a leader in the Gartner ranking."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"The best feature in Dataiku is that once the data is connected in the underneath layer, it flows exceptionally smoothly if you know how to tweak it."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"Traceability is vital since I manage many cohorts, and collaboration is key as I have multiple engineers substituting for one another."
"The best features Dataiku offers that help me with my demand forecasting and data science projects include having a complete overview of the flow directly from the flowchart, allowing me to observe all the steps in a single overview, and the ability to use a no-code, low-code node."
"Data Science Studio's data science model is very useful."
"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."
"The workspaces, which are like wrappers of Docker containers, made it easy to start development environments using Domino."
"The scalability of the solution is good; I'd rate it four out of five."
 

Cons

"The license is very expensive."
"Dataiku's scalability is not one of the best solutions to scale."
"There is room for improvement in terms of allowing for more code-based features."
"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. This is due to the fact that everything is enabled in a single window with different tabs. For them to actually develop and do the concurrent testing that needs to be done, it takes a bit of time. That is one improvement that I would like to see - from a web app developer perspective."
"The technical support from Dataiku is not good. The support team does not provide adequate assistance, and there are concerns about billing requests."
"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."
"The ability to have charts right from the explorer would be an improvement."
"The predictive analysis feature needs improvement."
"The deployment of large language models (LLMs) could be improved."
 

Pricing and Cost Advice

"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."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
9%
Manufacturing Company
9%
Energy/Utilities Company
6%
Financial Services Firm
38%
Insurance Company
8%
Manufacturing Company
8%
Healthcare Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise2
Large Enterprise11
No data available
 

Questions from the Community

What is your experience regarding pricing and costs for Dataiku Data Science Studio?
I find the pricing of Dataiku quite affordable for our customers, as they are usually large companies. However, it is a pricey solution and I primarily recommend it to bigger companies.
What needs improvement with Dataiku Data Science Studio?
I do not see anything that I would improve or enhance in Dataiku at this time; overall, it is a good tool to incorporate and to suggest to customers. Currently, I do not see anything specific that ...
What is your primary use case for Dataiku Data Science Studio?
We are a consulting firm for BFSI customers for the FSI value chain use cases, which is what we use Dataiku for, based on the problem statement the customer comes up with.
What needs improvement with Domino Data Science Platform?
The deployment of large language models (LLMs) could be improved. Currently, Domino provides a simple server that cannot handle big deployments, which is not suitable for LLMs.
What is your primary use case for Domino Data Science Platform?
We used Domino Data Science Platform for developing and working with machine learning models. It facilitated end-to-end development processes. Domino is based on Git, enabling collaboration similar...
What advice do you have for others considering Domino Data Science Platform?
It's important to have a DevOps team well-versed with cloud-native solutions to manage Domino effectively. Relying solely on data scientists might not be sufficient. I'd rate the solution eight out...
 

Also Known As

Dataiku DSS
Domino Data Lab Platform
 

Interactive Demo

Demo not available
 

Overview

 

Sample Customers

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
Allstate, GSK, AstraZeneca, Federal Reserve, US Navy, Bristol Myers Squibb, Bayer, BNP Paribas, Moodys, New York Life
Find out what your peers are saying about Dataiku vs. Domino Data Science Platform and other solutions. Updated: December 2025.
880,315 professionals have used our research since 2012.