We performed a comparison between Amazon SageMaker and Saturn Cloud based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."They are doing a good job of evolving."
"The most valuable feature of Amazon SageMaker for me is the model deployment service."
"The tool has made client management easier where patients need to upload their health records and we can use the tool to understand details on treatment date, amount, etc."
"The product aggregates everything we need to build and deploy machine learning models in one place."
"We were able to use the product to automate processes."
"The solution's ability to improve work at my organization stems from the ensemble model and a combination of various models it provides."
"Feature Store, CodeCommit, versioning, model control, and CI/CD pipelines are the most valuable features in Amazon SageMaker."
"The Autopilot feature is really good because it's helpful for people who don't have much experience with coding or data pipelines. When we suggest SageMaker to clients, they don't have to go through all the steps manually. They can leverage Autopilot to choose variables, run experiments, and monitor costs. The results are also pretty accurate."
"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."
"The feature I like the most about Saturn Cloud is that it has lightning-fast CPUs."
"There is plenty of computational resources (both GPU, CPU and disk space)."
"Creating notebook instances for multiple users is pretty expensive in Amazon SageMaker."
"Amazon SageMaker could improve in the area of hyperparameter tuning by offering more automated suggestions and tips during the tuning process."
"The documentation must be made clearer and more user-friendly."
"Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."
"Lacking in some machine learning pipelines."
"The payment and monitoring metrics are a bit confusing not only for Amazon SageMaker but also for the range of other products that fall under AWS, especially for a new user of the product."
"I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time."
"I would suggest that Amazon SageMaker provide free slots to allow customers to practice, such as a free slot to try out working with a Sandbox."
"Public Clouds integration and sandbox environments would be a true 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."
"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."
"We'd like to have the capability for installing more libraries."
Amazon SageMaker is ranked 5th in Data Science Platforms with 19 reviews while Saturn Cloud is ranked 8th in Data Science Platforms with 5 reviews. Amazon SageMaker is rated 7.4, while Saturn Cloud is rated 10.0. The top reviewer of Amazon SageMaker writes "Easy to use and manage, but the documentation does not have a lot of information". On the other hand, the top reviewer of Saturn Cloud writes "Great support, good availability, and seamless integration capabilities". Amazon SageMaker is most compared with Databricks, Azure OpenAI, Google Vertex AI, Domino Data Science Platform and Microsoft Azure Machine Learning Studio, whereas Saturn Cloud is most compared with Remote Desktop with Multi-user support by Aurora. See our Amazon SageMaker vs. Saturn Cloud report.
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