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SAP Predictive Analytics 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

SAP Predictive Analytics
Ranking in Data Science Platforms
27th
Average Rating
8.6
Reviews Sentiment
7.1
Number of Reviews
3
Ranking in other categories
No ranking in other categories
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 SAP Predictive Analytics is 0.9%, up from 0.4% 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%
SAP Predictive Analytics0.9%
Other98.6%
Data Science Platforms
 

Featured Reviews

AR
Senior Practice Manager - Head of SAP at a tech consulting company with 201-500 employees
Easy to implement, good data forecasting and reporting
This solution works for acquired data but not live, real-time data. If we connect it to a live backend system then we cannot perform predictive analytics on top of that. We have to first upload data to the cloud, manage the staging environment, and then perform the analysis. In the next release of this solution, I would like to see more automation in generating the models. The system can suggest the dimensions and measures that should be used, and pre-populate some of the information based on that. Power users would not have as much need for this, but this type of automation would be very helpful for business end-users.
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 most valuable features are the analytics and reporting."
"I think the features of the actual ability to forecast and pull trends and correlations has been really good."
"They provide a centralized space for data, code, and results."
"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."
"It offered an excellent development environment while not touching our production cloud resources."
"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."
"There is plenty of computational resources (both GPU, CPU and disk space)."
 

Cons

"This solution works for acquired data but not live, real-time data."
"Public Clouds integration and sandbox environments would be a true game changer."
"We'd like to have the capability for installing more libraries."
"It would be nice to have more hardware category options, like TPU coprocessors or ARM64 CPUs."
"Providing more detailed and beginner-friendly documentation, especially for advanced features, could greatly enhance the user experience."
"My main suggestion for improvement centers on pricing. Introducing a tier modelled after AWS spot instances would be a game-changer."
"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."
 

Pricing and Cost Advice

"The pricing is reasonable"
"A free trial version is available for testing out this solution."
Information not available
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Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise1
Large Enterprise3
 

Questions from the Community

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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

SAP BusinessObjects Predictive Analytics, BusinessObjects Predictive Analytics, BOPA
No data available
 

Overview

 

Sample Customers

mBank
Nvidia, Snowflake, Kaggle, Faeth, Advantest, Stanford University, Senseye and more.
Find out what your peers are saying about SAP Predictive Analytics vs. Saturn Cloud and other solutions. Updated: December 2025.
881,082 professionals have used our research since 2012.