Google Colaboratory is a popular platform for data scientists and machine learning scientists, but its limitations and pricing may not meet your needs. Several alternatives offer unique features and capabilities that cater to different data science needs and scenarios.
Follow the links to see the top Google Colab alternatives:
Deepnote for collaborative data visualizations
CoCalc for mathematics-based machine learning and data science
Kaggle Notebooks for learning from data science competitions
*Amazon SageMaker had some pricing examples in their website, this amount is based on those estimations. Users can customize their pricing.
**Reviews are based on Capterra and G2.
Why do data scientists prefer cloud-based platforms?
Cloud-based platforms offer scalable and flexible environments for data scientists to work on complex computations and data analysis. To train machine learning models, scientists need powerful hardware like GPUs and CPUs, but this is not always cost-effective.
In that case, switching to a cloud platform is popular among data scientists since they can access powerful computing resources, storage, and collaboration tools easily.
See if you are only interested in free cloud GPU alternatives.
What are the top 5 Google Colab alternatives?
Choosing the suitable GPU provider depends on various criteria, cloud-on prem deployment, usage of AI assistants, supported programming languages are some of them. In Table 2, you can see a comparison of Google Colab with its competitors.
Also, users should consider whether they work collaboratively, whether they need data visualizations, and their need for math features. The products are strongly varying in those areas. Below, you can read about our experience and suggestions:
Amazon SageMaker
Amazon SageMaker is a fully managed service that provides data scientists with the ability to build, train, and deploy machine learning models.
It offers one-click training and deployment, built-in ML algorithms, and scalability.
SageMaker is ideal for users who want to leverage the power of machine learning without worrying about the underlying infrastructure.
Kaggle Notebooks
Kaggle is a platform that offers a collaborative environment for data scientists and machine learning enthusiasts.
It provides access to a vast repository of datasets, kernels, and notebooks, and supports multiple programming languages.
Kaggle is ideal for users who want to participate in data science competitions, learn from others, and showcase their skills.
Deepnote
Deepnote is a collaborative data science platform that combines a code editor and a computational environment.
It offers real-time collaboration, customizable environments with an easy-to-use interface.
Users can easily make data visualizations.
Provides an AI assistant powered by gpt-4o.
Deepnote is ideal for collaborative working, especially for the teams in need of visualizing data.
CoCalc
CoCalc is a web-based cloud computing and course management platform for computational mathematics.
It offers real-time collaboration, integrated computational tools, and course management features.
With the usage of Jupyter, SageMath, LaTeX, and collaborative Linux terminal, it is suitable for academics, students, and researchers who want to collaborate on projects and learn from each other.
If users want to use AI assistants, they can choose between multiple LLM’s like ChatGPT, Gemini and Mistral, with free and priced options.
JupyterLab
JupyterLab is a next-generation web-based interface for Project Jupyter. It is an open-source platform.
JupyterLab is suitable for users who want a highly customizable and extensible platform for data science and machine learning.
Since JupyterLab uses your local system, you will be using your own hardware, so it is not the best option if you are looking for alternatives for more powerful GPUs.
FAQ
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE and NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and resources that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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