Google Colab vs Jupyter Notebook: Key Differences Explained

Creating, organizing, and sharing computer documents is essential in programming and data science. Most people turn to one of two popular tools (Google Colab and Jupyter Notebook) to help them manage their files.

SEE: Learn how to become a data scientist.

What is Google Colab?

Google Colab is a tool offered by Google Research that allows users to write and run Python code in their web browsers. Colab is based on the open source Jupyter and allows you to create and share calculation files hosted in the cloud without downloading or installing anything.

What is Jupyter notebook?

Jupyter is the original, free, open source, web-based interactive computing platform created from the IPython Project; Jupyter Notebook is a web application that allows users to create and share computational documents.

Google Colab vs Jupyter Notebook: comparison table

Google Colab and Jupyter Notebook: prices

Google Colab and Jupyter Notebook are free to use. Jupyter Notebook was released as an open source tool under the liberal terms of the modified BSD license, making it 100% free.

Although Google Colab is also free, you may need to pay for advanced features as your computing needs increase. The following are the paid plans offered by Google Colab:

• Pay what you consume: For this plan, there are no fixed subscription fees; You only pay for what you use.
• Pro Collaboration: For $9.99 a month, you get 100 compute units, access to machines with larger memory, and the ability to use a terminal with the virtual machine attached.
• Pro+ Collaboration: For $49.99 per month, you'll get 500 compute units, faster GPUs, and background execution capabilities.

Feature Comparison: Google Colab vs Jupyter Notebook

cloud based

The main differentiator of Google Colab from Jupyter Notebook is that it is cloud-based and Jupyter is not. If you work at Google Collab, you don't have to worry about downloading and installing anything on your hardware. It also means you can rest easy knowing that your work will be automatically saved and backed up to the cloud without you having to do anything.

Google Colab is great if you need to work on multiple devices, like one computer at home and another at work or a laptop and a tablet, because it syncs seamlessly between devices.

In contrast, Jupyter Notebook runs on your local machine and files are saved to your hard drive. Jupyter offers an auto-save interval that you can change, but it does not backup to the cloud. So, if your machine is affected, you're out of luck. Jupyter can't sync or share its files between devices without a third-party file-sharing service like Dropbox or GitHub.

Collaboration

We couldn't talk about Jupyter Notebook versus Google Colab without mentioning collaboration. As the name suggests, Google Colab is designed to make it easy to share your notebooks with anyone, even if you're not a data scientist. Other people can view your laptop without downloading any software, a big plus if you regularly work with non-technical people who need to access files.

Instead, anyone else must install Jupyter Notebook on their device to share their notebooks. This won't be a barrier if you only work with developers, data scientists, and other tech people who will already have Jupyter installed. If you work in a more diverse team, you may want to consider Google Colab because file sharing is easier.

Library installation

Since Google Colab is cloud-based, the tool comes pre-installed with several libraries. This means you don't have to set aside valuable disk space or time to download libraries manually. The free version also comes with a certain level of graphics processing units, memory and runtime, which may vary. You can upgrade to one of the paid plans if you need additional capacity. Google does not disclose limits for any of its Colab plans due to the need for flexibility.

With Jupyter Notebook, you will need to install each library you want to use on your device using pip or another package manager. You will also be limited by your computer's available RAM, disk space, GPU, and CPU. Having laptops stored on your hardware is more secure than in a third-party cloud. Therefore, manually installing the library can be advantageous for sensitive data.

R scripts

Both Google Colab and Jupyter Notebook allow users to run R scripts, although they are primarily designed for Python. In Google Colab, users can now choose to work with R by selecting it from the Runtime menu. For Jupyter Notebook, users must install an R kernel to work with R on their computer.

Pros and cons of Google Colab

Advantages

• Simple and easy to navigate interface.
• Access GPU and TPU runtimes for free.
• Import compatible data science and machine learning projects from other sources.
• Automatic version control similar to Google Docs.
• Collaboration capacity in real time.
• Integrates with other tools including GitHub, Jupyter Notebook, BLACKBOX AI, Codeium, CodeSquire, Google Workspace, Neptune.ai, StrongDM, Google Drive, and more.

Cons

• The free plan gives you limited resources.
• Some users reported issues with loading speed of new databases and data frames that are present offline.

Pros and cons of Jupyter Notebook

Advantages

• Modern, intuitive and interactive user interface.
• Supports markdown language for documentation.
• The interactive interface makes it easy for users to share images, code, and text in one place.
• Supports multiple programming languages ​​including Python, R, and Julia.

Cons

• Some users reported that the software became slow or crashed sometimes when working with large data sets or performing complex calculations.
• Some Jupyter Notebook users have reported that tracking changes and collaborating using version control tools like Git can be difficult because notebooks are stored as JSON files.

Should your organization use Google Colab or Jupyter Notebook?

Both Jupyter Notebook and Google Colab may be the right choice in particular circumstances. Google Colab is a great option for beginner developers or non-programmers who want to get started quickly without installing anything. It's also a great idea for anyone who needs to share notebook files with people who won't have the proper software installed on their devices.

Finally, Google Colab is a must-have for anyone looking to back up their work to the cloud and sync their laptops across multiple devices, but the ease of cloud sharing means less data security.

Meanwhile, Jupyter is best for sensitive files that need to be kept out of the cloud. Installing the laptops on your own hardware also means you never have to worry about your GPU or runtimes throttling, which can sometimes happen on free Colab accounts.

Review methodology

We reviewed both tools by collecting primary data from vendors' websites and documentation; This information includes features, pricing, and use cases. We also test each solution to get first-hand experience with its usability. To understand user experience, we evaluate feedback from current and former users of third-party review sites.

Ben Abbott updated this article in January 2024.