An Alternative to Databricks
Saturn Cloud offers a more low-cost infrastructure for scaling, collaborating, and optimizing resource management. Jump into a fully-managed environment and start training your model in seconds.












Comparing Saturn Cloud and Databricks
Saturn Cloud provides a data science platform that is more configurable and more interoperable than Databricks.
Platform Features | Saturn Cloud | Databricks |
---|---|---|
Ease of Use | ||
Approach | Saturn Cloud prioritizes ease of use while still allowing data scientist and teams access to large-scale computing resources. | Databricks prioritizes processing large data first and ease of use second. |
Interactive Environment | ||
Notebooks | Users employ JupyterLab and R, or they can SSH into their preferred IDE, meaning they can replicate their local environment. | Users work in a custom interactive notebook environment, with the limitations inherent to custom solutions. |
Tools & Workflow Flexibility | ||
Libraries | Users can install almost any library or package by utilizing pip, apt, conda, or a start script–minimizing dependency issues and maximizing flexibility. | Users utilize the custom workplace library system to install packages, the complexity of which could lead to dependency and runtime problems. |
Git Repositories | Full git functionality | Limited git functionality (i.e., one branch) |
Scalability & Performance | ||
Instance Types | Saturn Cloud’s upper range is 4 TB and 128 vCPUs, so users can run bigger workloads that require instances of these sizes. | Databricks maxes out at 768 GB of RAM and 96 vCPUs per instance for large-sized instances. |
Distributed Computing | Users can employ Dask clusters, which, for Python users, can not only be easier to debug and control but also be faster. | Users must employ Spark clusters with interface layers to their preferred languages, which can be more difficult to debug and can potentially be slower for some use cases. |
Loved by Engineers and AI Leaders
- Unleashing the full potential of open-source LLMs was made possible thanks to Saturn Cloud. Allowing me to add GPUs seamlessly immensely accelerated my experimentation process, providing a highly customized sandbox-like environment, ideal for any task that can benefit from the specialization of customized machine learning and data science.
- Saturn Cloud makes my work so much easier. When I sit down at the beginning of the day, I just want my environment to work. I want my favorite packages installed and available on demand. I want it to be easy to scale my workspace and have it shut down automatically when I'm done. Saturn Cloud solves all of that. Their customer service is also top-notch.
- Saturn Cloud is a great platform for training AI models. It is easy to use and has a user-friendly interface. I have used it to train BERT models, and it has helped me speed up the training process significantly. I would recommend Saturn Cloud to anyone looking to train AI models.
- Taking runtime down from 60 days to 11 hours is such an incredible improvement. We are able to fit in many more iterations on our models. This has a significant positive impact on the effectiveness of our product, which takes many iterations to perform at the standard necessary for our customers.
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