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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 May 2025, in the Data Science Platforms category, the mindshare of Alteryx is 6.1%, down from 7.8% compared to the previous year. The mindshare of Dataiku is 12.8%, up from 8.4% compared to the previous year. The mindshare of Domino Data Science Platform is 2.6%, down from 2.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
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 drag and drop and layout is simple to understand, with intuitive names of features."
"The most valuable feature for me is integration."
"It helps clean messy data and provides spatial analysis."
"I believe that the ability to leverage the gallery for scalability, as well as the general data blending functionality, is most beneficial to our core-based users."
"It is one of the most complete and great customer service that I experienced with a software company/ecosystem."
"The value add of Alteryx is the agility for making changes, and speed of deployment."
"The solution has a very strong community that is involved in the product. It helps make the usage easier and helps us find answers to our questions."
"I like that I can merge data from different sources into one place."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"One of the valuable features of Dataiku is the workflow capability."
"I rate the overall product as eight out of ten."
"The most valuable feature is the set of visual data preparation tools."
"Traceability is vital since I manage many cohorts, and collaboration is key as I have multiple engineers substituting for one another."
"The solution is quite stable."
"Dataiku is highly regarded as it is a leader in the Gartner ranking."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"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

"Alteryx can improve in data science. They have to have more features and components in the data science aspect because they claim to be a data science tool. However, in order to be more competitive, they have to improve on their data science propositions. Thre are other solutions on the market, such as other players in the market, Data2Go or DataIQ, and Alteryx needs to catch up."
"There are a few imputation techniques which they really need to include."
"They should make the solution user-friendly for nontechnical people by giving specific names to the options."
"The technical support could have a little bit of improvement."
"Deep learning models are not currently supported."
"We can't browse multiple files. When we deploy a solution on a gallery, let's say I have ten different files, and I have to upload them all at once. This is something that's difficult in the gallery. So case by case, I see some downsides, but often we do something alternative."
"It seems to me that it is not always user friendly."
"The interface could be improved."
"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"The technical support from Dataiku is not good. The support team does not provide adequate assistance, and there are concerns about billing requests."
"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."
"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"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 deployment of large language models (LLMs) could be improved."
"The predictive analysis feature needs improvement."
 

Pricing and Cost Advice

"We have a yearly cost that we pay for the licensing. We do not pay any costs in addition to the licensing fees."
"While it offers extensive features, including predictive analytics, for those who mainly use it for data preparation and blending, the cost can be prohibitive."
"Alteryx is generally more suited for medium—to large companies due to its potentially high licensing costs."
"There is a license required for this solution."
"The license is really expensive, we cannot afford to have two or three. It takes away all the budget of my area."
"The cost of Alteryx is approximately $2,900 annually."
"It is $4,000 a year, so it is cheap versus other solutions. It also accomplishes three times the volume on the job in the same time (as the other solutions).​"
"It can be a bit pricey, especially after the first year."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
24%
Computer Software Company
10%
Manufacturing Company
9%
Healthcare Company
6%
Financial Services Firm
17%
Educational Organization
12%
Manufacturing Company
9%
Computer Software Company
9%
Financial Services Firm
36%
Manufacturing Company
11%
Insurance Company
9%
Computer Software Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
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, Knime, Amazon Web Services (AWS) and others in Data Science Platforms. Updated: March 2025.
850,028 professionals have used our research since 2012.