Software Alternatives, Accelerators & Startups

Pandas VS Saturn Cloud

Compare Pandas VS Saturn Cloud and see what are their differences

Pandas logo Pandas

Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Saturn Cloud logo Saturn Cloud

ML in the cloud. Loved by Data Scientists, Control for IT. Advance your business's ML capabilities through the entire experiment tracking lifecycle. Available on multiple clouds: AWS, Azure, GCP, and OCI.
  • Pandas Landing page
    Landing page //
    2023-05-12
  • Saturn Cloud Homepage
    Homepage //
    2024-03-11

Saturn Cloud is an award-winning ML platform with 75,000+ users, including NVIDIA, CFA Institute, Snowflake, Flatiron School, Nestle, and more. It is an all-in-one solution for data science & ML development, deployment, and data pipelines in the cloud. Users can spin up a notebook with 4TB of RAM, add a GPU, connect to a distributed cluster of workers, build large language models, and more in a completely hosted environment.

Data scientists and analysts work best using the tools they want to use. You can use your preferred languages, IDEs, and machine-learning libraries in Saturn Cloud. We offer full Git integration, shared custom images, and secure credential storage, making scaling and building your team in the cloud easy. We support the entire machine learning lifecycle from experimentation to production with features like jobs and deployments. These features and built-in tools are easily shareable within teams, so time is saved and work is reproducible.

Pandas videos

Ozzy Man Reviews: Pandas

More videos:

  • Review - Ozzy Man Reviews: PANDAS Part 2
  • Review - Trash Pandas Review with Sam Healey

Saturn Cloud videos

Getting Started with Saturn Cloud

More videos:

  • Review - SATURN CLOUD || ECLIPSE || BLENDERS EYEWEAR || UNBOXING
  • Review - Saturn Cloud: Overview

Category Popularity

0-100% (relative to Pandas and Saturn Cloud)
Data Science And Machine Learning
Office & Productivity
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Development
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Pandas and Saturn Cloud

Pandas Reviews

25 Python Frameworks to Master
Pandas is a powerful and flexible open-source library used to perform data analysis in Python. It provides high-performance data structures (i.e., the famous DataFrame) and data analysis tools that make it easy to work with structured data.
Source: kinsta.com
Python & ETL 2020: A List and Comparison of the Top Python ETL Tools
When it comes to ETL, you can do almost anything with Pandas if you're willing to put in the time. Plus, pandas is extraordinarily easy to run. You can set up a simple script to load data from a Postgre table, transform and clean that data, and then write that data to another Postgre table.
Source: www.xplenty.com

Saturn Cloud Reviews

  1. One of the best cloud based solutions for data science projects

    Smooth and bug free experience. There are ready data science images with pre loaded packages for most common scenarios, making you focus on the project/problem and leave the infrastructure part to Saturn Cloud.

    👍 Pros:    Easy jupyter setup with boot scripts|Dask support|Easy to spin cluster for model training or grid search|Great and minimalistic ui
    👎 Cons:    Access to cheaper spot instances needed
  2. Amazing computes

    True story, way better than just sweating Colab. The best and cheapest compute services there is.

    👍 Pros:    Cheap price|Easy to use|Can use terminal
  3. An amazing cloud computing platform

    I have started using this to run the computations which generally require like 64+GB of RAM, and the procedure to setup the enviroment is also nice. Got all the R packages running smoothly.

    🏁 Competitors: Google Cloud Platform

The Best ML Notebooks And Infrastructure Tools For Data Scientists
Saturn Cloud hosts Jupyter Notebooks and has seamless management capabilities for Python environments on the cloud. You can start a project by creating a Jupyter notebook and selecting the disk space and your machine’s size. The configurations meet the requirements for most of the practical data science projects. Automatic version control, customisable environments, and a...

Social recommendations and mentions

Based on our record, Pandas seems to be a lot more popular than Saturn Cloud. While we know about 200 links to Pandas, we've tracked only 6 mentions of Saturn Cloud. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Pandas mentions (200)

  • Awesome List
    Pandas - A powerful data analysis and manipulation library for Python. Pandas Documentation - Official documentation. - Source: dev.to / 7 days ago
  • The ultimate guide to creating a secure Python package
    It's also possible for you to give a package an alias by using the as keyword. For instance, you could use the pandas package as pd like this:. - Source: dev.to / about 1 month ago
  • AWS Serverless Diversity: Multi-Language Strategies for Optimal Solutions
    Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience. - Source: dev.to / about 2 months ago
  • Pandas reset_index(): How To Reset Indexes in Pandas
    In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / about 2 months ago
  • Deploying a Serverless Dash App with AWS SAM and Lambda
    Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail.... - Source: dev.to / 4 months ago
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Saturn Cloud mentions (6)

  • Where to run computationally intensive analyses?
    Not 100% sure of your intention, but if you work with python, and you're familiar with (or can spend the time learning) dask, and willing to pay, you can consider coiled.io or saturncloud.io that offer managed dask that you can scale and use GPUs etc (again, not sure if applicable to your use case). Source: over 1 year ago
  • free-for.dev
    SaturnCloud - Data science cloud environment, that allows to run Jupyter notebooks and Dask clusters. 30 hours free computation and 3 hours of Dask per month. - Source: dev.to / over 1 year ago
  • [P] Serverless Jupyter Labs with GPUs, CPUs and high-speed storage
    I think your site looks good and I have used the type of service you offer, but there are 2 potential problems. As SheepherderPatient51 said,Google already offers all of this for free (and so does https://kaggle.com and https://www.paperspace.com ).  There are also other sites just like yours such as https://deepnote.com,https://saturncloud.io, and https://lambdalabs.com . Source: over 1 year ago
  • Show HN: Free Hosted JupyerLab with GPU
    * How does it differ from other GPU cloud providers that offer ready to use Jupyter notebooks? (E.g. https://support.genesiscloud.com/support/solutions/articles/47001170102-running-jupyter-notebook-or-jupyterlab-on-your-instance or https://saturncloud.io/). - Source: Hacker News / about 2 years ago
  • Partnership with Helium?
    At the moment I am going to go to https://saturncloud.io/ or https://www.cloudeo.group/. Source: over 2 years ago
View more

What are some alternatives?

When comparing Pandas and Saturn Cloud, you can also consider the following products

NumPy - NumPy is the fundamental package for scientific computing with Python

Deepnote - A collaboration platform for data scientists

OpenCV - OpenCV is the world's biggest computer vision library

Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Apache Zeppelin - A web-based notebook that enables interactive data analytics.