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Alteryx vs Cloudera Data Science Workbench 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 August 2025, in the Data Science Platforms category, the mindshare of Alteryx is 6.0%, down from 7.4% compared to the previous year. The mindshare of Cloudera Data Science Workbench is 1.3%, down from 1.6% 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
 

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.
Ismail Peer - PeerSpot reviewer
Useful for data science modeling but improvement is needed in MLOps and pricing
If you don't configure CDSW well, then it might be not useful for you. Deploying the tool can vary in complexity, but most of the time, it's relatively simple and straightforward. Triggering a job from data to production is easy, as the platform automates the deployment process. However, ensuring optimal resource allocation is essential for smooth operations.
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

"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."
"Alteryx is user-friendly and allows easy creation of workflows compared to Informatica PowerCenter."
"The cloud deployment ensures it scales easily."
"Shortens the time required to start analyzing data and looking for insights, minimizing the tasks that do not add value to the business and maximizing the analysis phase."
"I like the solution's velocity, the speed with which it processes data, and its ease of use."
"This is a drag-and-drop tool which is easy-to-use and yet can be customized by creating your own components."
"The product's initial setup phase is simple and straightforward."
"The drag and drop and layout is simple to understand, with intuitive names of features."
"The Cloudera Data Science Workbench is customizable and easy to use."
"I appreciate CDSW's ability to logically segregate environments, such as data, DR, and production, ensuring they don't interfere with each other. The deployment of machine learning is fast and easy to manage. Its API calls are also fast."
"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

"Alteryx is just as complicated as coding, in my opinion."
"Mastering Alteryx, a comprehensive solution, takes time. However, once you have gained proficiency with its layout and how to drag, drop, and connect components, it becomes remarkably easy, yet still thorough."
"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."
"It should have Linux support. It currently supports only Windows. It does not support any other platform. Its price should also be lower. Their US partner management program is actually unresponsive. One of the reasons why we don't have a formalized partnership plan with them is because their partner management team is atrociously unresponsive. This is something that they need to change."
"The solution could work on the BI side of the tool to make it a bit better."
"The server is too expensive for what you get and it really a designer desktop on a server."
"It would be great if Alteryx could take third party tools and incorporate them."
"I'd like it to be easier to work with PDF."
"Running this solution requires a minimum of 12GB to 16GB of RAM."
"The tool's MLOps is not good. It's pricing also needs to improve."
"The deployment of large language models (LLMs) could be improved."
"The predictive analysis feature needs improvement."
 

Pricing and Cost Advice

"Its price should be lower. The key thing that we see is that talking about ROI is an important element at the time of purchase. Cost becomes a factor in every discussion. Justifying the ROI for these kinds of workflows is always a challenge, and the only way to counter the challenge is by addressing the pricing."
"The cost of Alteryx is approximately $2,900 annually."
"ROI is huge. There are some secondary benefits, like analysts getting their post 5 PM time back or the ability to shorten all closing processes to a half or less."
"Alteryx isn't extortionately expensive, but it's not cheap either."
"I don't know much about the licensing, but there are some additional costs for certain features."
"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 solution has a more costly license than other tools in the market."
"The product is expensive."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
24%
Manufacturing Company
9%
Computer Software Company
9%
Retailer
5%
Financial Services Firm
34%
Healthcare Company
9%
Manufacturing Company
8%
Computer Software Company
8%
Financial Services Firm
38%
Manufacturing Company
10%
Insurance Company
8%
Computer Software Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
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 do you like most about Cloudera Data Science Workbench?
I appreciate CDSW's ability to logically segregate environments, such as data, DR, and production, ensuring they don'...
What needs improvement with Cloudera Data Science Workbench?
The tool's MLOps is not good. It's pricing also needs to improve.
What is your primary use case for Cloudera Data Science Workbench?
We have different use cases. Our banking use case uses machine learning to identify customer life events and recommen...
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
CDSW
Domino Data Lab Platform
 

Interactive Demo

Demo not available
Demo not available
 

Overview

 

Sample Customers

AnalyticsIq Inc., belk, BloominBrands Inc., Cardinalhealth, Cineplex, Dairy Queen
IQVIA, Rush University Medical Center, Western Union
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: July 2025.
864,574 professionals have used our research since 2012.