For Highly Opinionated Teams
Saturn Cloud is a data science workspace for teams who want to collaborate and scale easily. Work in the cloud with any IDE, including Jupyter and R. Run jobs, deployments, build dashboards and more. You know the what tools and process works best for you and care deeply about your work. Our built-in tools give you that flexibility to work the way you want.
Comparing Saturn Cloud and SageMaker
Saturn Cloud provides a data science platform that is more configurable, more powerful, and easier to use than SageMaker.
Ease of Use
|Simple, two-step start-up process:|
Users create an account and start a template project.
|Complex start-up process:|
Users need an AWS account, appropriate permissions, and an understanding of VPC creation, subnets, and AWS credentialing just to start up an instance.
Tools & Workflow Flexibility
|Versatile with built-in JupyterLab and R as well as easy SSH access||Does not natively support SSH connections|
|Images are designed to be as slim as possible and are regularly updated to keep users’ tools current.||Several default images are provided as kernels, but the images often have outdated versions of libraries.|
|Users can use their preferred ML libraries. Code is also transferable: Code written outside Saturn Cloud can be brought in, and code written inside Saturn Cloud can run in other workspaces.||Users are strongly encouraged to utilize AWS internal libraries. If they ever depart from the SageMaker ecosystem, the code they wrote using the AWS libraries may become obsolete, resulting in re-work and wasted time.|
Scalability & Performance
|Saturn Cloud’s upper range is 4 TB and 128 vCPUs, so users can run bigger workloads that require instances of these sizes.||SageMaker maxes out at 768 GB of RAM and 96 vCPUs per instance for large-sized instances.|
|Saturn Cloud makes Dask clusters first-class resources. Users simply fill out a one-page form to create and start a powerful Dask cluster in Saturn Cloud.||While SageMaker appears to offer a way to use Dask clusters, the process is incredibly difficult and requires users to manage cluster orchestration on their own.|
|Users have free access to GPU-based instances as well as Dask clusters. For as many months as users want, they have 30 hours per month of either 8 CPUs and 64GB RAM or 4 CPUs and a GPU. No credit card is required.||Users have a two-month free trial where they have access only to CPU-based images. Users have access to more hours of compute, but the instances are less powerful. This tier requires a credit card.|
|Saturn Cloud offers a paid tier: Hosted Pro. It includes unlimited compute resources, instances, and storage. Pricing is pay-as-you-go by the hour, and users receive a $20 free credit each month.||Users must pay after the two-month free trial. Base resources are sometimes cheaper than Saturn Cloud, however, because SageMaker relies on many different AWS services, users can be surprised with additional costs.|
Need a seamless and flexible alternative to SageMaker?
Choose Saturn Cloud.
With our open cloud environment, data scientists can work according to their unique business workflows, priorities, and needs, just as if they were working in their local environments. To learn more about the differences between Saturn Cloud and SageMaker, check out our comparison whitepaper.