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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
8.2
Reviews Sentiment
6.5
Number of Reviews
21
Ranking in other categories
No ranking in other categories
Domino Data Science Platform
Ranking in Data Science Platforms
17th
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 March 2026, in the Data Science Platforms category, the mindshare of Dataiku is 6.7%, down from 12.5% compared to the previous year. The mindshare of Domino Data Science Platform is 2.2%, down from 2.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Dataiku6.7%
Domino Data Science Platform2.2%
Other91.1%
Data Science Platforms
 

Featured Reviews

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.
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

"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."
"I believe the return on investment looks positive."
"The most valuable feature is the set of visual data preparation tools."
"Data Science Studio's data science model is very useful."
"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."
"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."
"One of the valuable features of Dataiku is the workflow capability."
"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."
"We primarily use the solution for customer retention, but there are a lot of use cases for this particular product."
"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

"Dataiku is down a lot of times, and we have to wait for sometimes five, ten, or fifteen minutes, after which it gets working again, and during those times, we are unable to get our work done."
"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"I need to stress upon the part about customer support because there are some product issues we have identified and raised with customer support, but sometimes the response is delayed, so that can be improved."
"The ability to have charts right from the explorer would be an improvement."
"I find that it is a little slow during use. When I use Dataiku to run my script to transfer data, it takes more time than I would expect for the operation to complete."
"All products have room for improvement, and I would like to see their pricing simplified, as it is somewhat complex."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"The deployment of large language models (LLMs) could be improved."
"The predictive analysis feature needs improvement."
"The predictive analysis feature needs improvement."
 

Pricing and Cost Advice

"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."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Manufacturing Company
10%
Computer Software Company
9%
Energy/Utilities Company
6%
Financial Services Firm
36%
Manufacturing Company
8%
Insurance Company
8%
Healthcare Company
6%
 

Company Size

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

Questions from the Community

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...
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: March 2026.
885,286 professionals have used our research since 2012.