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Saturn Cloud

Saturn Cloud | 1

Reviews from AWS Marketplace

9 AWS reviews
  • 9
  • 4 star
  • 3 star
  • 2 star
  • 1 star

External reviews

113 reviews
from G2

External reviews are not included in the AWS star rating for the product.

    Maciej B.

Scalable notebooks in my own AWS environment

  • November 18, 2021
  • Review verified by G2

What do you like best about the product?
Saturn makes it easy for our analysts to spin up Jupyter servers of any type on demand. The flexibility in being able to define custom docker images, startup scripts, etc. is phenomenal. I love the integration with Prefect Cloud, as it lets us seamlessly run our data ingestion pipeline using the same code and in the same environment as our analysts do their work. We run Saturn Enterprise in our own AWS environment, which keeps data moving quickly and meets our regulatory requirements of keeping data within our country. And if I ever run into trouble, Saturn's support always goes above and beyond to help out.
What do you dislike about the product?
With Saturn your end-user interface is the open-source Jupyter Lab ecosystem. Don't get me wrong, it's great. But services like DeepNote provide superior collaboration, SQL integrations, charting without code. I stick with Saturn as the best overall solution, but I am envious of their enduser experience.
What problems is the product solving and how is that benefiting you?
I needed an environment where a diverse team of data analysts could run the same notebooks without worrying about their local environment (Mac, Windows, Linux), and data transfer of files to and from cloud storage.They also needed to be able to access high-CPU machines on occasion. All these benefits were realized with Saturn, and then some.

    Joost v.

Excellent data science platform

  • November 17, 2021
  • Review verified by G2

What do you like best about the product?
Saturn Cloud makes it easy to spin up resources for your experiments or analysis. If you need to perform a large experiment on a lot of data, you can easily spin up a Dask cluster with multiple nodes, or if you need to train a machine learning model, it's easy to start a GPU instance. Onboarding new team members is simplified as everyone is using the same environment.
What do you dislike about the product?
Running hyperparameter searches can be done through Dask, but this does not always feel like the most natural way to perform this task. Having a jobs API that allows you to run arbitrary jobs similar to SLURM would be a helpful addition.
What problems is the product solving and how is that benefiting you?
Saturn cloud has allowed us to scale our experiments faster and simplified our way of working.

    Daniel B.

Streamlining my Data Science Workflow

  • November 15, 2021
  • Review verified by G2

What do you like best about the product?
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.
What do you dislike about the product?
Some parts of Saturn are a little wonky because it's run inside Docker containers. This makes containerized workflows difficult to deploy. I also wish it were easier to set up networked programs like Syncthing or database servers.
What problems is the product solving and how is that benefiting you?
Saturn Cloud makes it easy for anyone to spin up an environment for doing data analysis. It saves time and is less error-prone than being responsible for my own environment.

    Quantitative Development - Financial Services

Seminal Development in Python

  • December 23, 2020
  • Review verified by AWS Marketplace

Saturn Cloud has opened an entirely new door of opportunities for both the average quantitative developer and the deep learning expert.

At my company, I have been able to explore multiple new avenues for alpha generation that would have been unfeasible prior to the scale and speed introduced by Saturn.

I look forward to seeing the array of new applications developed as Saturn fuses the rapid development speed of Python with the raw power of distributed GPU computing while trivializing DevOps in the process.

    Sujit Pal

Seamless transition from local to cluster thanks to SaturnCloud

  • October 01, 2020
  • Review verified by AWS Marketplace

I used Saturn Cloud to run an NLP pipeline that I had started building locally (AWS t2.2xlarge) using Python (Jupyter notebooks), Dask, and SciSpacy, but which I was beginning to outgrow. Moving the code to SaturnCloud was quite painless -- all I had to do was to switch out the distributed Dask scheduler with the one provided by SaturnCloud, and re-point to S3 instead of local disk for my data. I would also like to thank the Saturn Cloud engineers, they are very professional and responsive, and without their timely help, my project would have taken much longer than it did. SaturnCloud also offers GPU machines for use with RAPIDS, and offers a Jupyter Lab environment as well. If you are using Dask and need to scale out, Saturn Cloud is a great way to do it without having to invest and set up your own cluster.


Great Product

  • September 15, 2020
  • Review verified by AWS Marketplace

In my opinion, this is the most best cloud hosted jupyter solution out there. The flexibility of scaling up and down as needed is great, as well as the seamless Dask integration. Not to mention the very responsive support team!


Easy way to run Dask and speed up model training

  • August 07, 2020
  • Review verified by AWS Marketplace

You get an integrated Jupyter Lab + Dask cluster management environment, which makes it straightforward to parallelize model training and get a big speedup. Collaboration is built-in as well.


When you absolutely, positively need to parallelize all the data

  • August 06, 2020
  • Review verified by AWS Marketplace

Dask is a very powerful library that allows for parallel execution of python code across essentially arbitrary compute resources. I've used dask previously on a smaller scale for things like out-of-memory processing of very large dataframes too big to fit into ram on a respectable workstation.

Dask can take almost any job and make it as much faster as you want, depending on the number of processing nodes and their network connections, and your ability to create, debug, and maintain a distributed dask cluster. The latter of these can be quite a painful challenge to overcome.

We are very happy with the service that Saturn provides as they solve both of these issues at once. Their distributed client can autoscale the number of nodes in its cluster using whatever ec2 instance type thats needed and it plays very nicely cuda, which can be quite tricky (frustrating) to properly configure.

Executing the same code across multiple nodes equipped with their own cpu/gpu/ram is what makes a supercomputer super. Saturn essentially makes it convenient to rent a python-based supercomputer with whatever desired specifications limited only by the hardware available on aws and your vpc quota.

    one happy jovyan

Low maintenance, high performance

  • April 29, 2020
  • Review verified by AWS Marketplace

Before Saturn, I wasted a ton of time trying to manage my team's JupyterHub. What began as a fun little project quickly turned into a maintenance nightmare. Saturn eliminated all the hassle. The environment just works. Within minutes we can go from one small, basic instance to multiple 64-core servers crunching big data. What's even more exciting is Saturn keeps getting better. New and useful features keep showing up, making it easier for my team to do great work. I'm looking forward to working with Saturn for a long time to come!


Fast Setup, Easy to Use

  • March 31, 2020
  • Review verified by AWS Marketplace

I used Saturn Cloud for a Machine Learning project that trained a network intrusion classier using PCAP data. In a few minutes I was coding in a jupyter notebook without having to worry about data privacy, and collaboration was simple. The ease of setup and computational power available make this a great collaboration tool, and I will definitely be using again.