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Rockset vs Saturn Cloud 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:
 

Categories and Ranking

Rockset
Ranking in AWS Marketplace
41st
Average Rating
8.0
Reviews Sentiment
8.2
Number of Reviews
2
Ranking in other categories
Vector Databases (17th)
Saturn Cloud
Ranking in AWS Marketplace
14th
Average Rating
10.0
Reviews Sentiment
7.5
Number of Reviews
6
Ranking in other categories
Data Science Platforms (10th)
 

Mindshare comparison

As of May 2025, in the AWS Marketplace category, the mindshare of Rockset is 0.1%, down from 0.3% compared to the previous year. The mindshare of Saturn Cloud is 0.1%, down from 0.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AWS Marketplace
 

Featured Reviews

Raghavendra Sao - PeerSpot reviewer
Used to get data from the database faster
Rockset is an easy tool, and anyone can use it. The solution provides some type of data grouping. This grouping of data based on some parameters is not simple, but it is very useful. I would recommend the solution to other users. Overall, I rate the solution an eight out of ten.
Alessandro Trinca Tornidor - PeerSpot reviewer
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

"Rockset is very fast, and you can query just like in MySQL."
"The initial setup was very simple."
"It didn't take long to see that Saturn Cloud could scale with my needs, providing more resources when required."
"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)."
"They provide a centralized space for data, code, and results."
"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."
 

Cons

"Filtering the database based on indexes is difficult in Rockset and should be simplified."
"Rockset is now bought by OpenAI. It’s uncertain if Rockset will continue to exist as it is."
"It would be nice to have more hardware category options, like TPU coprocessors or ARM64 CPUs."
"We'd like to have the capability for installing more libraries."
"Public Clouds integration and sandbox environments would be a true game changer."
"My main suggestion for improvement centers on pricing. Introducing a tier modelled after AWS spot instances would be a game-changer."
"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."
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Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What needs improvement with Rockset?
For our use, there is no room for improvement. It depends on how you use it, however, from our perspective, it has met our needs.
What is your primary use case for Rockset?
We used Rockset as an SQL interface on some of DynamoDB. Our use case is primarily for customer-facing data reporting.
What advice do you have for others considering Rockset?
Rockset is now bought by OpenAI. It’s uncertain if Rockset will continue to exist as it is. OpenAI may have its own agenda for it. They have started canceling some contracts with customers, so this...
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 ...
 

Overview

 

Sample Customers

1. Adobe 2. Cisco 3. Comcast 4. DoorDash 5. Expedia 6. Facebook 7. GitHub 8. IBM 9. Lyft 10. Microsoft 11. Netflix 12. Oracle 13. Pinterest 14. Reddit 15. Salesforce 16. Slack 17. Spotify 18. Square 19. Target 20. Twitter 21. Uber 22. Verizon 23. Visa 24. Walmart 25. Yelp 26. Zoom 27. Airbnb 28. Dropbox 29. eBay 30. Google 31. LinkedIn 32. Amazon
Nvidia, Snowflake, Kaggle, Faeth, Advantest, Stanford University, Senseye and more.
Find out what your peers are saying about Rockset vs. Saturn Cloud and other solutions. Updated: April 2025.
850,028 professionals have used our research since 2012.