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Alteryx 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

Alteryx
Ranking in Data Science Platforms
5th
Average Rating
8.4
Reviews Sentiment
7.0
Number of Reviews
82
Ranking in other categories
Predictive Analytics (1st), Data Preparation Tools (1st)
Domino Data Science Platform
Ranking in Data Science Platforms
14th
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 July 2025, in the Data Science Platforms category, the mindshare of Alteryx is 5.9%, down from 7.5% compared to the previous year. The mindshare of Domino Data Science Platform is 2.7%, 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.
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

"This is a drag-and-drop tool which is easy-to-use and yet can be customized by creating your own components."
"The support is very good."
"Alteryx is a simple and easy-to-use solution."
"I like the fact that you can easily blend data from different platforms."
"Automation is the most valuable aspect for us. The ability to wrap business logic around the data is very helpful."
"The most valuable feature of Alteryx is its stand-alone version that we do not have to download dependencies for loads. Additionally, the scan is useful for beginners."
"It saves time on a lot projects. ​"
"The scheduling within the solution is excellent."
"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

"The solution could improve in the visualization."
"Its most valuable feature lies in its functionality."
"A feature which allows the user to be able to click on an output (in a file browser) and see the creation of the module would be fantastic."
"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."
"Deep learning models are not currently supported."
"Alteryx can improve the model management and deployment processing of large workloads."
"Configuration is very low."
"It is a little bit pricey."
"The predictive analysis feature needs improvement."
"The deployment of large language models (LLMs) could be improved."
 

Pricing and Cost Advice

"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).​"
"In order to have designers, and, if you want to collaborate, you have to buy a server. If the designer is $5,000, and if you want a server, you have to pay $80,000."
"The price could be better."
"It can be a bit pricey, especially after the first year."
"The pricing is $5000 per year per production license."
"In my opinion, it's actually quite expensive."
"I rate the solution's pricing as a ten, as it is highly priced."
"My organization pays for it, and I do not look into the financial aspect of the licensing, but I know it is pretty expensive."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
24%
Computer Software Company
10%
Manufacturing Company
9%
Retailer
5%
Financial Services Firm
38%
Manufacturing Company
10%
Insurance Company
7%
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 directly if you want to know more.
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, R integrations if your team requires this. It can handle over 2 billion rows of...
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 the following: - An excellent desktop tool for Data Prep and analytics. - Featu...
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

No data available
Domino Data Lab Platform
 

Interactive Demo

Demo not available
 

Overview

 

Sample Customers

AnalyticsIq Inc., belk, BloominBrands Inc., Cardinalhealth, Cineplex, Dairy Queen
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 Alteryx vs. Domino Data Science Platform and other solutions. Updated: June 2025.
860,168 professionals have used our research since 2012.