Anaconda Notebooks vs Saturn Cloud

Anaconda Notebooks puts JupyterLab in a cloud environment for writing, editing, and running Python code through an Anaconda Cloud account. Users can start data science and AI projects in a browser with packages and computing resources supplied by the service, without installing Python locally. Two preconfigured environments are available: one with the latest Anaconda Distribution packages and another with packages selected for AI workflows. Notebooks can be shared by URL so others can open a copy, work with it through an Anaconda account, or download it. Outputs can be deployed as web applications using Panel. Anaconda Assistant for Python can analyze tables and suggest ways to work with data, while Data Connectors let users save CSV files on Anaconda Cloud for Excel or notebook access. The Free plan costs nothing and includes 5 GB cloud storage. Starter costs $15 a month, billed monthly, with 10 GB storage per user. Organizations may block notebook sharing, resulting in a 403 error when a user tries to share.

Saturn Cloud is a control plane for GPU clouds that turns GPU fleets into token-metered AI services. It orchestrates bare metal, managed Kubernetes, and managed Slurm through one control plane. Supported workloads include inference endpoints, training and fine-tuning, and development workspaces with JupyterLab, VS Code, SSH, and persistent storage. Listed languages are Python, R, Julia, and Java, with Jupyter Notebook files supported. Each customer receives a separate Kubernetes or Slurm cluster by default, without shared scheduler, etcd, or admission webhooks. GPU-hour and inference-token use can be metered by user, project, and tenant, with invoice data available through an API and Snowflake view. Enterprise deployments can run in a customer’s cloud account, and Enterprise data can remain in AWS. Hosted access has a free plan, while resource usage requires Pro. Hosted Pro is billed pay-as-you-go hourly; storage is listed at 0.10 USD per GB-month.