Dataiku vs Domino Data Science Platform comparison

Why PeerSpot?

Dataiku and Domino Data Lab are both solutions in the Data Science Platforms category. Dataiku is ranked #2 with an average rating of 8.2, while Domino Data Lab is ranked #17 with an average rating of 8.0. Dataiku holds a 4.5% mindshare in Data Science Platforms, compared to Domino Data Lab’s 1.8% 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

7,896 Views
7,738 Comparison Views

100% willing to recommend

Domino Data Science Platform

Read 2 Domino Data Science Platform reviews

1,944 Views
1,925 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: September 2026).

Buyer's Guide

Dataiku vs. Domino Data Science Platform

September 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

17th

Average Rating

7.6

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of September 2026, in the Data Science Platforms category, the mindshare of Dataiku is 4.5%, down from 12.4% compared to the previous year. The mindshare of Domino Data Science Platform is 1.8%, down from 2.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Mindshare Distribution
Product	Mindshare (%)
Dataiku	4.5%
Domino Data Science Platform	1.8%
Other	93.7%

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.

Read full review

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

"Using Dataiku has meant that we spend less time on preparing and cleaning data, and we spend less time on blending models together, ultimately meaning that we can spend more time modeling."

"I believe the return on investment looks positive."

"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."

"The solution is quite stable."

"Traceability is vital since I manage many cohorts, and collaboration is key as I have multiple engineers substituting for one another."

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

"Cloud-based process run helps in not keeping the systems on while processes are running."

"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."

More Dataiku pros

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

"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."

Cons

"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."

"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."

"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."

"All products have room for improvement, and I would like to see their pricing simplified, as it is somewhat complex."

"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."

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

"The ability to have charts right from the explorer would be an improvement."

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

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

18%

Manufacturing Company

10%

Computer Software Company

Comms Service Provider

Financial Services Firm

35%

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.

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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 8% of the time

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Compared 5% of the time

Microsoft Azure Machine Learning Studio vs Dataiku

Compared 3% of the time

More Dataiku Competitors

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Compared 11% of the time

KNIME Business Hub vs Domino Data Science Platform

Compared 7% of the time

Alteryx vs Domino Data Science Platform

Compared 6% of the time

SAS Enterprise Miner vs Domino Data Science Platform

Compared 5% of the time

Amazon SageMaker vs Domino Data Science Platform

Compared 4% of the time

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Product Reports

Buyer's Guide

Dataiku

September 2026

Download Dataiku product report

Buyer's Guide

Data Science Platforms

September 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

September 2026

Free Report: Dataiku vs. Domino Data Science Platform

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