Creating, organizing, and sharing computational documents is essential in programming and data science. Most people use 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 hosted computing files in the cloud without having to download or install anything.
What is Jupyter Notebook?
Jupyter is the original free and open source web-based interactive computing platform that originated 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
| Software | ||
|---|---|---|
| Starting price | ||
| Free plan | ||
| Cloudy | ||
| File synchronization | ||
| File sharing | ||
| Library installation | ||
| View file without installation |
Google Colab and Jupyter Notebook: Pricing
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 grow. Google Colab offers the following paid plans:
- Pay as you go: There are no fixed subscription fees for this plan; you only pay for what you use.
- Colab Pro: For $9.99 a month, you get 100 compute units, access to machines with higher memory, and the ability to use a terminal with a virtual machine attached.
- Colab Pro+: For $49.99 a month, you get 500 compute units, a faster GPU, and the ability to run in the background.
Feature Comparison: Google Colab Vs. Jupyter Notebook
Cloudy
The main difference that sets Google Colab apart from Jupyter Notebook is that it is cloud-based, and Jupyter is not. If you work in Google Collab, you don’t have to worry about downloading and installing anything on your hardware. It also means you can rest easy knowing your work is 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, such as one computer at home and one at work, or a laptop and tablet, because it syncs seamlessly between devices.
In contrast, Jupyter Notebook runs on your local computer and files are stored on your hard drive. Jupyter offers an auto-save interval that you can change, but it doesn’t back up to the cloud. So if your machine is affected, you’re out of luck. Jupyter can’t sync or share your files between devices without a third-party file sharing service like Dropbox or GitHub.
Cooperation
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 they’re not a data scientist. Other people can view your laptop without downloading any software – a big advantage if you regularly work with non-techies who need to access files.
Conversely, anyone else needs to install Jupyter Notebook on their device to share their notebooks. This won’t be a hindrance if you work exclusively with developers, data scientists, and other technical people who 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 with various libraries pre-installed. This means you don’t have to dedicate precious disk space or time to manually download libraries. The free version also comes with a certain level of GPUs, memory and runtime, which may vary. If you need more capacity, you can upgrade to one of the paid plans. Due to the need for flexibility, Google does not publish limits for any of its Colab plans.
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 notebooks stored on your hardware is more secure than in a third-party cloud. Therefore, manually installing the library may be more sensitive data.
RScripts
Both Google Colab and Jupyter Notebook allow users to run R scripts, even though they are primarily 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 the R core to work with R on their computer.
Pros and cons of Google Colab
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- Straightforward 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 version control similar to Google Docs.
- Ability to collaborate in real time.
- It integrates with other tools, including GitHub, Jupyter Notebook, BLACKBOX AI, Codeium, CodeSquire, Google Workspace, Neptune.ai, StrongDM, Google Drive, and more.
Disadvantages
- The free plan gives you limited resources.
- Some users have reported problems with the loading speed of new databases and dataframes that are present offline.
Advantages and Disadvantages of Jupyter Notebook
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- Modern, intuitive and interactive user interface.
- It supports a markup language for documentation.
- The interactive interface makes it easy for users to share images, code and text in one place.
- It supports multiple programming languages, including Python, R, and Julia.
Disadvantages
- Some users have reported that the software slows down or sometimes crashes when working with large datasets or performing complex calculations.
- Some Jupyter Notebook users have reported that tracking changes and collaboration using version control tools like Git can be complicated because notebooks are stored as JSON files.
Should your organization use Google Colab or Jupyter Notebook?
In some circumstances, both Jupyter Notebook and Google Colab can be the right choice. Google Colab is an excellent choice for entry-level 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 laptop files with people who don’t have the correct software installed on their devices.
Finally, Google Colab is a must-have for anyone who wants to back up their work to the cloud and sync their notebooks between multiple devices — but easy cloud sharing means less data security.
Meanwhile, Jupyter is better for sensitive files that need to be kept off the cloud. Installing notebooks on your own hardware also means you’ll never have to worry about limiting your GPU or runtimes, which can sometimes happen with free Colab accounts.
Review methodology
We tested both tools by collecting primary data from vendor websites and documentation; this information includes features, pricing and use cases. We also tested each solution to gain first-hand experience of its usability. To learn about user experience, we evaluate feedback from current and past users from third-party review sites.
Ben Abbott updated this article in January 2024.