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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
6th
Average Rating
8.4
Reviews Sentiment
7.0
Number of Reviews
84
Ranking in other categories
Predictive Analytics (1st), Data Preparation Tools (1st)
Domino Data Science Platform
Ranking in Data Science Platforms
18th
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 February 2026, in the Data Science Platforms category, the mindshare of Alteryx is 3.8%, down from 6.5% compared to the previous year. The mindshare of Domino Data Science Platform is 2.2%, down from 2.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Market Share Distribution
ProductMarket Share (%)
Alteryx3.8%
Domino Data Science Platform2.2%
Other94.0%
Data Science Platforms
 

Featured Reviews

Rajneesh Prajapati - PeerSpot reviewer
Senior Rpa Consultant at Accely Consulting
Time-saving workflows have transformed data preparation and predictive analysis for my team
Some of the best features Alteryx offers are its no and low-code capabilities. It delivers massive time-saving and includes spatial and predictive analysis. Alteryx includes built-in tools such as drive time analysis and linear regression, which are much harder to achieve in standard BI tools such as Power BI or Tableau. In addition to these features, Alteryx provides built-in spatial tools that can calculate drive time and location-based insights with minimal effort through drag-and-drop spatial tools, low complex coding, faster, and more accurate results. Linear regression predicts sales based on marketing spend, estimates costs based on usage, and identifies trends in historical data. Alteryx has positively impacted my organization by saving time, improving accuracy, and enabling better decision-making. Using Alteryx, complex tasks such as data cleansing, joining datasets, drive time analysis, and linear regression can be done much faster compared to manual Excel or SQL work. This reduces dependency on manual effort and lowers the risk of human error. Drive time analysis helps my organization make better location-based decisions, such as identifying optimal service areas or improving customer reach.
AS
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…

Quotes from Members

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

Pros

"The ease-of-use allows non-technical business users to directly create their own solutions without the use of additional development resources."
"The filtering is fast, and it provides a search tool that is great."
"The most valuable feature is user-friendliness, as Alteryx can be used by those without any coding experience or experienced data scientists as it has the functionality to embed R and Python scripts."
"I found Alteryx's ability to modify data on the fly, using in-memory processing, very useful."
"The most valuable feature of this solution is data preparation."
"Technical support is very helpful."
"The most valuable feature of Alteryx is the intelligence suite."
"There are a lot of good customization capabilities."
"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

"Sometimes workflows tend to queue up, and they tend to get canceled for some reason that we don't know sometimes."
"The technical support could have a little bit of improvement."
"The only area where the product lags is documentation and videos on the analytical app and the batch macro."
"The product's pricing needs improvement."
"Pricing flexibility can be better, especially for small teams and organizations, as the current licensing cost can be a barrier for wider adoption."
"There are no ready models to use in analytics."
"Configuration is very low."
"The solution can be made more affordable."
"The deployment of large language models (LLMs) could be improved."
"The predictive analysis feature needs improvement."
 

Pricing and Cost Advice

"The designer has a list price of $5,995 USD."
"It's very expensive. I'd rate it a four out of ten in terms of the price. It's great for big companies but not for small companies."
"While it offers extensive features, including predictive analytics, for those who mainly use it for data preparation and blending, the cost can be prohibitive."
"It's probably on the pricey side, but they provide some really useful ways to grow and test."
"There is a license required for this solution."
"We use the free version of the solution. There are enterprise licenses available. It cost approximately $5,000 annually. It is an expensive solution and there are additional features that cost more money."
"My organization pays for it, and I do not look into the financial aspect of the licensing, but I know it is pretty expensive."
"Alteryx isn't extortionately expensive, but it's not cheap either."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
21%
Manufacturing Company
9%
Computer Software Company
7%
Retailer
5%
Financial Services Firm
39%
Manufacturing Company
8%
Insurance Company
8%
Healthcare Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business32
Midsize Enterprise15
Large Enterprise53
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: December 2025.
881,733 professionals have used our research since 2012.