Dataiku vs Domino Data Science Platform comparison

Dataiku and Domino Data Lab are both solutions in the Data Science Platforms category. Dataiku is ranked #2 with an average rating of 8.1, while Domino Data Lab is ranked #18 with an average rating of 8.0. Dataiku holds a 5.6% mindshare in Data Science Platforms, compared to Domino Data Lab’s 2.1% mindshare. Additionally, 100% of Dataiku users are willing to recommend the solution, compared to 100% of Domino Data Lab users who would recommend it.

Dataiku

Read 21 Dataiku reviews

6,883 Views
6,745 Comparison Views

100% willing to recommend

Domino Data Science Platform

Read 2 Domino Data Science Platform reviews

1,618 Views
1,602 Comparison Views

100% willing to recommend

Dataiku

Domino Data Science Platform

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

Dataiku and Domino Data Science Platform are competing products in the data science and analytics space. Dataiku seems to have the upper hand in ease of use and support, while Domino excels in feature offerings and flexibility.

Features: Dataiku is recognized for its collaborative environment, data preparation tools, and user-friendly machine learning capabilities. Domino Data Science Platform features an open ecosystem that allows for flexibility and integration with various tools and platforms, offering deeper customization that appeals to teams looking for more control over data science operations.

Ease of Deployment and Customer Service: Dataiku offers a smooth deployment process supported by robust customer assistance. In contrast, Domino Data Science Platform provides a flexible deployment model that can be tailored to fit specific business requirements but may require more technical involvement. Dataiku's responsive customer service complements its ease of deployment, whereas Domino offers flexibility at the expense of increased complexity.

Pricing and ROI: Dataiku provides competitive setup costs and delivers substantial ROI through its simplicity and speed of deployment. Domino Data Science Platform may be more costly initially, but it promises a high ROI through its extensive feature set and flexibility that supports diverse data science projects, often making the decision dependent on budget constraints versus the desired level of customization and complexity.

To learn more, read our detailed Dataiku vs. Domino Data Science Platform Report (Updated: April 2026).

Buyer's Guide

Dataiku vs. Domino Data Science Platform

April 2026

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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

2nd

Average Rating

8.2

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Domino Data Science Platform

Ranking in Data Science Platforms

18th

Average Rating

7.6

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of May 2026, in the Data Science Platforms category, the mindshare of Dataiku is 5.6%, down from 12.8% compared to the previous year. The mindshare of Domino Data Science Platform is 2.1%, down from 2.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Mindshare Distribution
Product	Mindshare (%)
Dataiku	5.6%
Domino Data Science Platform	2.1%
Other	92.3%

Data Science Platforms

Featured Reviews

Shubhamkumar Gomar

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.

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AHMEDSAHRAOUI

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…

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Quotes from Members

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

Pros

"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."

"Dataiku is highly regarded as it is a leader in the Gartner ranking."

"Technical support is really, really good."

"The solution is quite stable."

"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."

"Extremely easy to use with its GUI-based functionality and large compatibility with various data sources. Also, maintenance processes are much more automated than ever, with fewer errors."

"Compared to Informatica, this tool is extremely easy with its GUI-based functionality and large compatibility with various data sources, and maintenance processes are much more automated than ever, with fewer errors."

"I rate the overall product as eight out of ten."

More Dataiku pros

"The workspaces, which are like wrappers of Docker containers, made it easy to start development environments using Domino."

"We primarily use the solution for customer retention, but there are a lot of use cases for this particular product."

"The scalability of the solution is good; I'd rate it four out of five."

Cons

"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."

"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."

"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 license is very expensive."

"One area for improvement is the need for more capabilities similar to those provided by NVIDIA for parallel machine learning training. We still encounter some integration issues."

"I think it would help if Data Science Studio added some more features and improved the data model."

"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."

"The technical support from Dataiku is not good. The support team does not provide adequate assistance, and there are concerns about billing requests."

More Dataiku cons

"The deployment of large language models (LLMs) could be improved."

"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

19%

Manufacturing Company

Computer Software Company

Energy/Utilities Company

Financial Services Firm

37%

Manufacturing Company

Insurance Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	6
Midsize Enterprise	2
Large Enterprise	13

No data available

Questions from the Community

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...

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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...

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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...

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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.

See all answers

What is your primary use case for Domino Data Science Platform?

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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...

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Comparisons

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Compared 5% of the time

Amazon SageMaker vs Dataiku

Compared 5% of the time

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Databricks vs Domino Data Science Platform

Compared 14% of the time

KNIME Business Hub vs Domino Data Science Platform

Compared 9% of the time

Alteryx vs Domino Data Science Platform

Compared 6% of the time

Amazon SageMaker vs Domino Data Science Platform

Compared 5% of the time

Anaconda Business vs Domino Data Science Platform

Compared 4% of the time

More Domino Data Science Platform Competitors

Product Reports

Buyer's Guide

Dataiku

May 2026

Download Dataiku product report

Buyer's Guide

Data Science Platforms

April 2026

Download Domino Data Science Platform product report

Also Known As

Dataiku DSS

Domino Data Lab Platform

Interactive Demo

Demo not available

Dataiku

Domino Data Lab

Overview

Dataiku Data Science Studio is acclaimed for its versatile capabilities in advanced analytics, data preparation, machine learning, and visualization. It streamlines complex data tasks with an intuitive visual interface, supports multiple languages like Python, R, SQL, and scales efficiently for large dataset handling, boosting organizational efficiency and collaboration.

Dataiku

Domino Data Science Platform fosters collaboration by integrating data exploration, model training, and deployment into a unified hub tailored to data professionals' needs.

Advanced features make Domino a go-to choice for organizations aiming to streamline their data science workflows. It empowers teams to significantly enhance productivity by simplifying processes for data exploration, model training, and deployment. The platform's robust capabilities facilitate collaboration, ensuring models are delivered efficiently and effectively. With its scalable infrastructure, Domino supports the growing demands of data-centric businesses, enabling them to derive actionable insights swiftly.

What are the key features of Domino Data Science Platform?

Collaborative Workspaces: Allows teams to work seamlessly using shared environments.
Model Management: Streamlines the lifecycle from experimentation to production.
Scalable Infrastructure: Adapts to growing data and computational needs.
Integrated Tools: Supports popular data science tools and languages.
Version Control: Tracks changes in projects and models for accountability.

What are the benefits and ROI of using Domino Data Science Platform?

Enhanced Productivity: Boosts team efficiency by automating repetitive tasks.
Cost Efficiency: Reduces overhead by optimizing resource use.
Data-driven Decisions: Speeds up the time to insight with efficient processes.
Improved Collaboration: Facilitates teamwork through unified platforms.
Scalability: Provides flexibility to accommodate business growth.

Domino is implemented across industries including finance, healthcare, and retail, delivering tailored solutions that support data-driven strategies. In finance, it optimizes investment analytics; in healthcare, it enhances predictive modeling for patient outcomes; in retail, it refines customer insights for better engagement.

Domino Data Lab

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

Buyer's Guide

Dataiku vs. Domino Data Science Platform

April 2026

Free Report: Dataiku vs. Domino Data Science Platform

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