Google COLAB VS JUPYTER: Explanation of key differences

Creating, organizing and sharing computing documents is necessary in programming and data sciences. Most people turn to one of two popular tools – Google Colab and Jupyter laptop – to help them manage their files.

See: Learn how to become a scientist da data.

Google Colab icon.
Image: Google Colab

What is Google Colab?

Google Colar is a tool offered by Google research that allows users to write and perform the Python code in its web browsers. COLAB is based on Open Source Jupyter and allows you to create and share hosted computer files in the cloud without downloading or installing anything.

Jupyter icon.
Picture: Jupyter

What is Jupyter’s notebook?

Jupyter is the original free, open-source, web interactive computing platform that is spinning from the IPython project; Jupyter is a web application that allows users to create and share computing documents.

Google COLAB vs. JUPYTER Notebook: Comparative Table

Software
Google Colar
JUPYTER Notebook
Initial price
9.99 $ monthly
Release
Free plan
Yes
Yes
Cloud -based
Yes
No
File synchronization
Yes
No
File sharing
Yes
No
Library installation
No
Yes
View the file without installation
Yes
Yes

Notebook Google Colab and Jupyter: Prices

The Google Colab and Jupyter notebook can be used free of charge. The Jupyter notebook has been released as an open source code under liberal conditions modified by the BSD license, which is 100% free for use.

Although Google Colab is also free, you may need to pay for advanced features because your computing needs are increasing. Below are paid plans offered by Google Corab:

  • Pay: There are no fixed fees for this plan for this plan; You only pay for what you use.
  • COLAB PRO: For $ 9.99, you get 100 computing units, access to higher memory machines and the ability to use a terminal with a connected virtual computer.
  • COLAB PRO+: For $ 49.99, you get 500 computing units, faster GPUs and background performance.

Function Comparison: Google Colab vs. JUPYTER Notebook

Cloud

Google Colab’s chief Jupyter laptop is that it is based on the cloud and Jupyter is not. If you work on Google Collage, you don’t have to work on downloading and installing your hardware. This also means that you can easily relax with knowing that your work will be automatically showing and backing up to the cloud without having to do anything.

Google Colab's homepage.
Google Colab’s homepage.

Google Colab is great if you need to work on multiple devices – for example, one computer at home and one at work or laptop and tablet – because it is smoothly synchronizing across devices.

On the other hand, the Jupyter notebook is running on a local computer and the files are stored on the hard drive. Jupyter offers an automatic control interval that you can change but does not deal with the cloud. Therefore, if your machine is influenced, you are lucky. Jupyter cannot synchronize or share your files across devices without third -party file sharing services such as Dropbox or Github.

Dashboard layout on Jupyter notebook.
Dashboard layout on Jupyter notebook.

Cooperation

We couldn’t talk about Jupyter versus Google Colab without mentioning cooperation. As the name suggests, Google CoB creates to make it easier to share laptops with anyone – even if they are not on data scientists. Other people can view your laptop without downloading any software – a big ad – even if you regularly work with Netechies who need access to files.

A instrument panel for an experience that can be shared by Google Colab.
A instrument panel for an experience that can be shared by Google Colab.

Anyone else has to install Jupyter on their device to share their notebooks. This will not be an obstacle if you only work with developers, data scientists and other technological people who will already have Jupyter installed. If you are working on a more diverse team, you may want to consider Google Colab because file sharing is easier.

Library installation

Self Google Colar is based on the cloud, the tool is preinstalled with different libraries. This means that you do not have to separate the space for a precious disk or the time to download libraries manually. The free version also comes with a certain level of graphic units, memory and running times that can fluctuate. If additional capacity is needed, you can upgrade to one of the paid plans. Google does not publish the limits for any of its COLAB plans due to the need for flexibility.

With Jupyter, you will need to install every library you would like to use ontto your device using a PIP or other package manager. You will also be limited by the available RAM, disk space, GPU and CPU. Having laptops stored on hardware is safer than in a third party cloud. Therefore, the installation of a manual library can be more for sensitive data.

R scripts

Both Google Colab and Jupyter allow users to operate R scripts, even if the primary designed for Python. At Google Colab, users can now choose to work with R selection on the run menu. With the Jupyter notebook, users must install a rore to work on their computer with R.

The advantages and disadvantages of Google Colab

Proprietary

  • A direct interface that is easy to navigate.
  • Free access to GPU and TPU Runtims.
  • Import compatible machine learning and science projects about data from other sources.
  • Automatic control of similar Google documents.
  • The ability to cooperate in real time.
  • The integrates with other tools included Github, Jupyter, BlackBox AI, Codeium, Codesquire, Google Workspace, Neptun.ai, Strongdm, Google Dident.

Disadvantages

  • The free plan gives you limited resources.
  • Some users report from the speed of new databases and data frames that are present offline.

The advantages and disadvantages of Jupyter Notebook

Proprietary

  • Modern, intuitive and interactive user interface.
  • Language designation supports the documentation.
  • The interactive interface makes it easier for users to share images, code and text in one place.
  • More programming languages, including Python, R, Julia.

Disadvantages

  • Some users have said that software sometimes sometimes slows down or crashes when working with large data sets or performing complex calculations.
  • Some notebook users have stated that changing and collaboration of monitoring tools such as GIT can be complicated because notebooks of note are stored as JSON files.

Should your organization use Google Colab or Jupyter?

Both Jupyter and Google Colab can be the right choice in specific circumstances. Google Colab is an excellent choice for a basic level or non -program who wants to start fast without installing anything. It is also a great idea for anyone who needs to share laptops with people who will not install the right software on their devices.

Google Colar is a necessity for anyone who wants to back up your work to the cloud and synchronize your laptops on multiple devices – but ease of cloud sharing means reduced data security.

Meanwhile, Jupyter is better for a sensitive file that must be detained outside the cloud. Installing laptops on your own hardware also means that you never need to work about how your GPU or Runtimes is suppressed, which can sometimes happen on your account without free collaboration.

Review Methodology

Both tools are checked by collecting primary data from the website and supplier documentation; This information included functions, prices and use of boxes. We also tested each solution to gain first -hand experience with its usability. In order to read about the experience of users, we have evaluated the feedback of current and past users from third -party audit sites.

Ben Abbott updated this article in January 2024.

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