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SAS Enterprise Miner vs Saturn Cloud 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

SAS Enterprise Miner
Ranking in Data Science Platforms
23rd
Average Rating
7.6
Reviews Sentiment
6.2
Number of Reviews
13
Ranking in other categories
Data Mining (7th)
Saturn Cloud
Ranking in Data Science Platforms
17th
Average Rating
10.0
Reviews Sentiment
7.5
Number of Reviews
6
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of January 2026, in the Data Science Platforms category, the mindshare of SAS Enterprise Miner is 1.6%, up from 0.7% compared to the previous year. The mindshare of Saturn Cloud is 0.5%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Market Share Distribution
ProductMarket Share (%)
Saturn Cloud0.5%
SAS Enterprise Miner1.6%
Other97.9%
Data Science Platforms
 

Featured Reviews

reviewer1352853 - PeerSpot reviewer
Executive Head of analytics at a retailer with 5,001-10,000 employees
A stable product that is easy to deploy and can be used for structured and unstructured data mining
We use the solution for predictive analytics to do structured and unstructured data mining I like the way the product visually shows the data pipeline. The product must provide better integration with cloud-native technologies. I have been using the solution for 20 years. The product is very…
Alessandro Trinca Tornidor - PeerSpot reviewer
Sviluppatore software at TeamSystem
Good for creating POCs, training machine learning models, and experimenting without local resources
The project I’m currently working on relies on CUDA, but my local PC does not have any Nvidia GPUs. I’ve found the computational resources and ease of use provided by Saturn Cloud invaluable. Also, there are many ready-to-use Docker images and a rich documentation portal with useful examples. The dashboard for creating a new virtual environment contains almost all the features I needed: environment variable definitions, git repositories cloning directly from the new resources page, and an edit field to define a custom script during the boot process. For this reason, Saturn Cloud.io is a very good solution for creating POCs, training machine learning models, and generally experimenting a bit without worrying about local resources.

Quotes from Members

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

Pros

"The setup is straightforward. Deployment doesn't take more than 30 minutes."
"Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic."
"Good data management and analytics."
"The most valuable feature is the decision tree creation."
"The technical support is very good."
"I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically with PS400), and automation of several tasks."
"The solution is able to handle quite large amounts of data beautifully."
"he solution is scalable."
"They provide a centralized space for data, code, and results."
"The feature I like the most about Saturn Cloud is that it has lightning-fast CPUs."
"It didn't take long to see that Saturn Cloud could scale with my needs, providing more resources when required."
"It offered an excellent development environment while not touching our production cloud resources."
"Saturn Cloud supports GPU as part of the environment, which is essential for many computational tasks in machine learning projects. It also allows us to edit the environment, including the image, before we start the cloud resources. This feature lets us quickly set up the environment without the hassle of moving the data and code to another cloud device."
"There is plenty of computational resources (both GPU, CPU and disk space)."
 

Cons

"Technical support could be improved."
"While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system."
"The product must provide better integration with cloud-native technologies."
"The user interface of the solution needs improvement. It needs to be more visual."
"The solution is much more complex than other options."
"Virtualization could be much better."
"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."
"The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch."
"Providing more detailed and beginner-friendly documentation, especially for advanced features, could greatly enhance the user experience."
"Saturn Cloud should include prebuilt images for advanced data science packages like LightGBM in the next release. If possible, they should also provide a Kaggle image, which contains the most common Python packages used in machine learning."
"My main suggestion for improvement centers on pricing. Introducing a tier modelled after AWS spot instances would be a game-changer."
"It would be nice to have more hardware category options, like TPU coprocessors or ARM64 CPUs."
"Public Clouds integration and sandbox environments would be a true game changer."
"We'd like to have the capability for installing more libraries."
 

Pricing and Cost Advice

"The solution must improve its licensing models."
"The solution is expensive for an individual, but for an enterprise/institution (purchasing bulk licenses), it is not a high price for the use that will come from it."
"This solution is for large corporations because not everybody can afford it."
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Top Industries

By visitors reading reviews
Financial Services Firm
25%
Educational Organization
11%
Manufacturing Company
10%
University
9%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise4
Large Enterprise7
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise1
Large Enterprise3
 

Questions from the Community

Ask a question
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What do you like most about Saturn Cloud?
There is plenty of computational resources (both GPU, CPU and disk space).
What needs improvement with Saturn Cloud?
My main suggestion for improvement centers on pricing. Introducing a tier modelled after AWS spot instances would be a game-changer. Users could bid on unused compute capacity, potentially leading ...
What is your primary use case for Saturn Cloud?
I'm leveraging a cloud-based platform for competitive machine learning. Tight deadlines and resource-intensive models demand powerful hardware. The cloud provides scalable GPUs and RAM, letting me ...
 

Also Known As

Enterprise Miner
No data available
 

Overview

 

Sample Customers

Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare
Nvidia, Snowflake, Kaggle, Faeth, Advantest, Stanford University, Senseye and more.
Find out what your peers are saying about SAS Enterprise Miner vs. Saturn Cloud and other solutions. Updated: December 2025.
881,114 professionals have used our research since 2012.