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Alteryx vs Dataiku vs Domino Data Science Platform comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

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

Mindshare comparison

As of September 2025, in the Data Science Platforms category, the mindshare of Alteryx is 5.9%, down from 7.3% compared to the previous year. The mindshare of Dataiku is 12.3%, up from 10.3% compared to the previous year. The mindshare of Domino Data Science Platform is 2.7%, down from 2.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Market Share Distribution
ProductMarket Share (%)
Alteryx5.9%
Dataiku12.3%
Domino Data Science Platform2.7%
Other79.1%
Data Science Platforms
 

Featured Reviews

Theresa McLaughlin - PeerSpot reviewer
Quick development enables seamless data processing despite occasional support issues
There were times when the product would fail during development without an apparent reason. The support structure changed; initially, we received great support, however, it later became less reliable due to licensing issues and a tiered support system. Licensing negotiations were problematic, affecting our product usage. For instance, our licenses were temporarily lost during negotiations when an agreement couldn't be reached.
RichardXu - PeerSpot reviewer
The platform organizes workflows visually and efficiently
One of the valuable features of Dataiku is the workflow capability. It allows us to organize a workflow efficiently. The platform has a visual interface, making it much easier for educated professionals to organize their work. This feature is useful because it simplifies tasks and eliminates the need for a data scientist. If you are knowledgeable about AI, you can directly write using primitive tools like Pantera flow, PyTorch, and Scikit-learn. However, Dataiku makes this process much easier.
AS
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 initial setup is easy."
"It offered quick development, with the ability to process large datasets."
"The solution offers excellent predicting power. The accuracy and confidence have been great."
"The ease-of-use allows non-technical business users to directly create their own solutions without the use of additional development resources."
"The modeling features are very good."
"The most valuable feature of this solution is data preparation."
"It is a stable and scalable solution."
"One-stop shop for data preparation, blending, prediction, and optimization in a single workflow."
"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."
"The most valuable feature is the set of visual data preparation tools."
"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."
"The solution is quite stable."
"If many teams are collaborating and sharing Jupyter notebooks, it's 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."
"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 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."
 

Cons

"There are a few hiccups with specific data sets and languages or formats that the data comes in. That may be a minor problem, but we can work through it. We had some issues looking at XML format in added data, but it wasn't significant."
"The solution could work on the BI side of the tool to make it a bit better."
"They can provide some pre-built tools for predictive analytics instead of us having to build all the tools. It should also be improved from the visualization aspect. It should have better visualization capabilities. There are tools out there that have better visualization capabilities, which Alteryx is lacking currently."
"Alteryx can improve the model management and deployment processing of large workloads."
"The data integration component could most likely be improved to increase enterprise scalability."
"Configuration is very low."
"We are hoping that the NLP features will also support Chinese characters."
"There are a few imputation techniques which they really need to include."
"The license is very expensive."
"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."
"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"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."
"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."
"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."
"The predictive analysis feature needs improvement."
"The deployment of large language models (LLMs) could be improved."
 

Pricing and Cost Advice

"It is an expensive solution."
"The price could be better."
"The cost of the solution could be reduced."
"While it offers extensive features, including predictive analytics, for those who mainly use it for data preparation and blending, the cost can be prohibitive."
"The license is really expensive, we cannot afford to have two or three. It takes away all the budget of my area."
"The designer has a list price of $5,995 USD."
"A designer and scheduler for $13K/year in total is pretty much earning you the money back in time and in other resources."
"Alteryx is an expensive solution."
"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
23%
Manufacturing Company
9%
Computer Software Company
9%
Retailer
6%
Financial Services Firm
18%
Manufacturing Company
10%
Computer Software Company
9%
Energy/Utilities Company
6%
Financial Services Firm
39%
Manufacturing Company
10%
Insurance Company
8%
Computer Software Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise14
Large Enterprise51
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise1
Large Enterprise7
No data available
 

Questions from the Community

What is the Biggest Difference Between Alteryx and IBM SPSS Modeler?
One of the differences is that with Alteryx you can use it as an ETL and analytics tool. Please connect with me direc...
What is the Biggest Difference Between Alteryx and IBM SPSS Modeler?
Alteryx is an extremely easy and flexible data tool, flexible in terms of drag and drop toolset and also has python, ...
What is the Biggest Difference Between Alteryx and IBM SPSS Modeler?
I am not familiar with IBM SPSS Modeler, therefore, I cannot compare these two products. Regarding Alteryx I can say...
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...
What needs improvement with Dataiku Data Science Studio?
There is room for improvement in terms of allowing for more code-based features. I would love for Dataiku to allow mo...
What is your primary use case for Dataiku Data Science Studio?
My company sells licenses for both Dataiku and Alteryx, and we have clients who use them. I engage with several compa...
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 can...
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-e...
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 so...
 

Also Known As

No data available
Dataiku DSS
Domino Data Lab Platform
 

Interactive Demo

Demo not available
Demo not available
 

Overview

 

Sample Customers

AnalyticsIq Inc., belk, BloominBrands Inc., Cardinalhealth, Cineplex, Dairy Queen
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 Databricks, Amazon Web Services (AWS), Knime and others in Data Science Platforms. Updated: August 2025.
866,483 professionals have used our research since 2012.