Creating, organizing, and sharing computational documents is essential to programming and data science. Most people use one of two popular tools to help manage files: Google Colab and Jupyter Notebook.
Note: Learn how to become a data scientist.
What is Google Colab?
Google Colab is a tool provided by Google Research that allows users to write and run Python code in a web browser. Colab is based on the open source Jupyter and allows you to create and share cloud-hosted computation files without having to download or install anything.
What is Jupyter Notebook?
Jupyter is the first free and open source web-based interactive computing platform derived from the IPython project. Jupyter Notebook is a web application that allows users to create and share computational documents.
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quick base
Number of employees by company size
Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+)
Small (50-249 employees), medium (250-999 employees), large (1,000-4,999 employees), enterprise (5,000+ employees)
Small, medium, large, enterprise
characteristic
Agile development, analytics/reports, APIs, etc.
Google Colab and Jupyter Notebook: Comparison Chart
| software | ||
|---|---|---|
| starting price | ||
| Free plan | ||
| cloud based | ||
| file sync | ||
| file sharing | ||
| Install libraries | ||
| View files without installing |
Google Colab and Jupyter Notebook: Pricing
Both Google Colab and Jupyter Notebook are free to use. Jupyter Notebook is released as an open source tool under the liberal terms of the Modified BSD License, making it 100% free to use.
Google Colab is also free, but as your computing needs grow, you may need to pay for more advanced features. The paid plans offered by Google Colab are as follows:
- Pay as you go: There is no fixed subscription fee for this plan. You only pay for what you use.
- Collaboration Pro: For $9.99 per month, you get 100 compute units, access to higher memory machines, and the ability to use the terminal with connected virtual machines.
- Collaboration Pro+: For $49.99 per month, you get 500 compute units, faster GPUs, and background execution.
Feature Comparison: Google Colab vs Jupyter Notebook
cloud based
The main difference between Jupyter Notebook and Google Colab is that it is cloud-based whereas Jupyter is not. If you’re working in Google Collab, you don’t have to worry about downloading and installing anything on your hardware. This also means you can rest assured that your work is automatically saved and backed up to the cloud without you having to do anything.
Google Colab syncs seamlessly across multiple devices, which is great if you need to work across multiple devices—your home computer, your work computer, your laptop, and your tablet.
Jupyter Notebook, on the other hand, runs on your local computer and files are stored on your hard disk. Jupyter provides an automatic save interval that you can change but does not back up to the cloud. So if your computer is affected, you are out of luck. Jupyter cannot sync or share files across devices without a third-party file sharing service like Dropbox or GitHub.
collaboration
You can’t discuss Jupyter Notebook and Google Colab without mentioning collaboration. As the name suggests, Google Colab was created to make it easy to share notebooks with anyone, even if you’re not a data scientist. Other people can view your laptop without downloading any software. This is a huge advantage if you regularly work with non-experts who need access to your files.
Conversely, if you want to share a notebook, the other person must also install Jupyter Notebook on their device. This won’t be a hindrance if you work alone with developers, data scientists, and other technical staff who already have Jupyter installed. If you work in a more diverse team, you might consider Google Colab because it makes file sharing easier.
Install libraries
Since Google Colab is cloud-based, the tool comes with a variety of libraries pre-installed. This means you don’t have to separate out valuable disk space or time to download libraries manually. The free version includes certain levels of graphics processing units, memory, and runtime, which may vary. If you need more capacity, you can upgrade to one of our paid plans. Google does not disclose limits for Colab plans due to the need for flexibility.
With Jupyter Notebook, you need to install each library you want to use on your device using pip or another package manager. It is also limited by your computer’s available RAM, disk space, GPU, and CPU. Storing your laptop on your hardware is more secure than storing it in a third-party cloud. Therefore, manual library installation may be helpful for sensitive data.
R script
Google Colab and Jupyter Notebook allow you to run R scripts, although they are primarily designed for Python. In Google Colab, users can now choose to work with R by selecting R within the runtime menu. Jupyter Notebook requires users to install the R kernel to use R on their computer.
Advantages and disadvantages of Google Colab
merit
- Simple interface that is easy to navigate.
- Get free access to GPU and TPU runtimes.
- Import compatible machine learning and data science projects from other sources.
- Automatic versioning similar to Google Docs.
- Real-time collaboration features.
- Integrates with other tools including GitHub, Jupyter Notebook, BLACKBOX AI, Codeium, CodeSquire, Google Workspace, Neptune.ai, StrongDM, Google Drive, and more.
disadvantage
- The free plan offers limited resources.
- Some users have reported issues with the speed of loading new databases and dataframes that are offline.
Advantages and disadvantages of Jupyter Notebook
merit
- Modern, intuitive and interactive user interface.
- Supports Markdown language for documentation.
- The interactive interface allows users to easily share images, code, and text in one place.
- Supports multiple programming languages including Python, R, and Julia.
disadvantage
- Some users have reported that the software sometimes slows down or crashes when working with large data sets or performing complex calculations.
- Some Jupyter Notebook users have reported that because notebooks are stored as JSON files, tracking changes and collaborating using version control tools like Git can be complicated.
Should your organization use Google Colab or Jupyter Notebook?
In certain situations, both Jupyter Notebook and Google Colab may be the right choice. Google Colab is a great choice for new developers or non-programmers who want to get started quickly without installing anything. It’s also a good idea for anyone who needs to share laptop files with people who don’t have the appropriate software installed on their devices.
Lastly, Google Colab is a must-have for anyone who wants to back up their work to the cloud and sync their notebooks across multiple devices. But the ease of cloud sharing means less secure data.
On the other hand, Jupyter is better for sensitive files that need to be stored in the cloud. By installing your laptop on its own hardware, you don’t have to worry about GPU or runtime limitations that can sometimes occur with Colab free accounts.
Review Methodology
We reviewed both tools by collecting baseline data from the vendor’s website and documentation. This information includes features, pricing, and use cases. We also tested each solution and experienced first-hand its usability. To find out about user experience, we evaluated feedback from current and past users on third-party review sites.
Ben Abbott updated this article in January 2024.
