Saturn Cloud is an ML platform for individuals and teams, available on multiple clouds: AWS, Azure, GCP, and OCI. It provides access to computing resources with customizable amounts of memory and power, including GPUs and Dask distributed computing clusters, in a wholly hosted environment. Saturn Cloud is presented as flexible and straightforward for new data scientists while giving senior and experienced staff the
capabilities and configurability they need.…
$10
hourly $5 credit purchase to start
Pricing
Saturn Cloud
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Saturn Cloud
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Yes
Free/Freemium Version
Yes
Premium Consulting/Integration Services
No
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No setup fee
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Saturn Cloud
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Saturn Cloud
Verified User
Engineer
Chose Saturn Cloud
The Availability of Saturn Cloud is way better than Vertex Workbench . I even have trouble initiating instances
Like said earlier the main keypoint being more compute time . This is the single most advantage Saturn Cloud has over others. This enables us to first try and then eventually move onto Saturn Cloud for the work making it a smooth experience and a rewarding one to say the least.
unlike google colab, the free part of saturn cloud is much more robust. I recently tried to train some BERT models with some data, and to be honest, colab was lagging behind in terms of processing and ram. also, the paid part is much more expensive compared to saturn cloud.
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Runtimes are not automatically deleted, transparent free resources: 30hrs a month, persistent disk of 10 GB. The pricing on the premium plan is transparent. No credits that get deleted after 90 days. Possibility to run ipynb notebooks that were written in an IDE, no need to …
Saturn Cloud is an exceptional data science platform that offers a multitude of advantages to organizations. It excels in simplifying and optimizing data science workflows, providing scalable infrastructure resources, and promoting efficient collaboration among teams. With its …
We chose Saturn Cloud over other tools like Databricks and Google CoLab because:1. Easy to Use: Saturn Cloud is simple and fun, just like working on a notebook.2. Sizing Help: Saturn Cloud lets us use bigger or smaller computers when we need them, saving money and time.3. Super …
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I have used AWS EC2 , GCP Compute Instance, Paperspace Gradient etc.
I have selected Saturn Cloud since it provides cost effective and also more reliable and available compute machines compared to the above list.
Saturn Cloud provides an R server, that's super important. Even you can write R on CoLab with different settings, but it is inconvenient and slow. Saturn Cloud can give me a different IDE environment that I'm more used to, even if I'm using Python. Whereas CoLab is more …
Saturn cloud has a niche market, being a reseller of cloud instances, it ofcourse has a higher cost than the giants but Saturn Cloud is well-suited for organizations that want a cloud-based data science platform that is easy to use and scalable. AWS, GCP, and Azure are more …
It has more free resources to use. Nowadays, all platforms are using the cloud, so I currently use it often. Previous platforms are being used in local host environments. Local host = not so much usage of resources. Cloud platforms = High usage of free resources and …
Saturn Cloud is way cheaper as compared to AWS Sage Maker, and also easy to use we get a notebook setup with the correct environment on the click of a single button. The UI is also a bit simpler and understandable which helps in explaining non-tech individuals and reduces the …
Saturn Cloud is a powerful data science platform that offers numerous benefits to organizations. It simplifies and streamlines the development, deployment, and scaling of data science and machine learning models. The platform addresses common business problems such as scalability, collaboration, efficiency, and cost-effectiveness. With Saturn Cloud, organizations can easily handle large datasets and complex computations, collaborate effectively among data science teams, automate repetitive tasks, optimize workflows, and utilize flexible and cost-efficient cloud resources. By leveraging Saturn Cloud, organizations can accelerate their data science projects, improve productivity, and achieve better outcomes in areas such as predictive modeling, recommendation systems, fraud detection, and more.
While Saturn Cloud offers a range of pre-built templates and workflows, there is currently limited support for customization. For example, users may not be able to modify the pre-configured environments that come with the templates, or may find it difficult to integrate their own custom libraries and tools. Offering more flexibility in this area could help users tailor the platform to their specific needs and workflows.
While Saturn Cloud offers a variety of pre-built environments for data science and machine learning workloads, some users may prefer to use custom Docker images instead. However, the platform currently has limited support for Docker, which can be a limitation for users who need to work with specific dependencies or custom libraries. Adding more robust support for Docker could help to make the platform more versatile and adaptable to a wider range of use cases.
This is user friendly , better than its counterparts. Anyone familiar working with other cloud solutions for GPU will agree on this. Hence the rating of 10 was given to this. I personally love the fact that I get so much compute time for being a free user which is very efficient in terms of budget
Saturn Cloud provides an R server, that's super important. Even you can write R on CoLab with different settings, but it is inconvenient and slow. Saturn Cloud can give me a different IDE environment that I'm more used to, even if I'm using Python. Whereas CoLab is more dedicated to Jupyter notebook
Although we are still in the implementation phase with Saturn Cloud, we anticipate significant positive impacts on our business objectives.
The platform is expected to enhance our computational capabilities with its easy access to top-tier NVIDIA GPUs, which should accelerate our AI and machine learning projects. We believe this will lead to reduced development times and faster deployment of our generative AI models.
While Saturn Cloud provides excellent computational resources and reliable uptime, I find that their user interface could be improved. The UI can be unintuitive at times, making it a bit challenging to navigate and configure certain settings. Enhancing the user interface to be more streamlined and user-friendly would significantly improve the overall experience. Having pre-configured stacks readily available would also save time and make the platform even more efficient to use.