Software Alternatives, Accelerators & Startups

nbviewer.org VS Deepnote

Compare nbviewer.org VS Deepnote and see what are their differences

nbviewer.org logo nbviewer.org

Rackspace server host Jupyter Notebooks from your github repo

Deepnote logo Deepnote

A collaboration platform for data scientists
  • nbviewer.org Landing page
    Landing page //
    2023-03-19
  • Deepnote Landing page
    Landing page //
    2023-10-09

nbviewer.org features and specs

  • Simple Viewing
    nbviewer.org allows for easy rendering of Jupyter Notebook files directly in the browser without needing to run a Jupyter server locally.
  • Read-Only Access
    Notebooks are rendered in a read-only format, so users do not need to worry about accidental modifications while viewing.
  • No Installation Required
    Users don't need to install any software to view notebooks, which is beneficial for quick sharing with people who do not have Jupyter installed.
  • Supports Multiple File Sources
    Supports notebooks from various sources including URLs, GitHub repositories, and uploaded files.

Possible disadvantages of nbviewer.org

  • Lack of Interactivity
    Since nbviewer renders notebooks in a static, read-only mode, users cannot interact with the code or execute cells.
  • Dependency on External Hosting
    Requires access to hosted content, which may be unavailable if the source server is down or if there are network issues.
  • Security Concerns
    Hosting a notebook publicly via a URL or GitHub can expose sensitive data if not properly managed, as nbviewer does not provide authentication or access control.
  • No Offline Access
    Users need an internet connection to use nbviewer, which limits its utility in offline scenarios.

Deepnote features and specs

  • Collaborative Features
    Deepnote allows for real-time collaboration, similar to Google Docs, where multiple users can work on the same notebook simultaneously without conflicts.
  • Integration with Popular Tools
    Deepnote integrates seamlessly with popular data sources and tools such as Google Drive, GitHub, and SQL databases, enhancing its versatility for data science projects.
  • User-Friendly Interface
    The interface is clean and easy to navigate, making it accessible for both beginners and experienced data scientists.
  • Cloud-Based
    Being a cloud-based solution, Deepnote eliminates the need for local setup and maintenance, allowing users to access their projects from anywhere with internet access.
  • Data Security
    Deepnote provides robust security features, ensuring that your data and notebooks are protected against unauthorized access.
  • Integrated Version Control
    Version control within Deepnote allows users to track changes, revert to previous versions, and collaborate more effectively on shared projects.

Possible disadvantages of Deepnote

  • Limited Offline Access
    As a cloud-based platform, Deepnote requires an internet connection for most of its functionality, which can be a limitation for users needing offline access.
  • Performance Constraints
    Heavy computational tasks might be limited by the performance capabilities of the cloud resources provided, affecting users who require extensive computational power.
  • Subscription Costs
    While there is a free tier, advanced features and increased resource limits come at a subscription cost, which might be a consideration for students or hobbyists.
  • Learning Curve for Advanced Features
    While basic functionality is user-friendly, mastering the more advanced features and integrations may require a learning curve, especially for users new to data science tools.
  • Dependency on External Infrastructure
    The performance and availability of Deepnote can be affected by issues with their cloud service providers, which adds a layer of dependency on external infrastructure.

Analysis of Deepnote

Overall verdict

  • Deepnote is an excellent tool for data scientists, particularly those who value collaboration and need interactive, shareable notebooks. Its user-friendly interface and powerful integration capabilities make it a strong contender in the data science notebook space.

Why this product is good

  • Deepnote is a collaborative data science notebook designed to enhance productivity and simplify the data science workflow. It offers real-time collaboration, similar to Google Docs, making it easier for teams to work together efficiently. It supports various programming languages and integrates seamlessly with popular tools such as Jupyter notebooks, Git, and cloud storage services. Deepnote also provides a strong focus on data visualization and interactive dashboards, making it easier to interpret and present data insights.

Recommended for

  • Data scientists who work in teams and need a collaborative environment.
  • Professionals who require seamless integration with existing tools and cloud storage.
  • Users who prioritize interactive data visualization and interpretability.
  • Educators looking for an accessible platform to teach data science concepts.

nbviewer.org videos

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Deepnote videos

Could this be the Best Data Science Notebook? (Deepnote)

Category Popularity

0-100% (relative to nbviewer.org and Deepnote)
Data Science And Machine Learning
Data Science Notebooks
100 100%
0% 0
Productivity
0 0%
100% 100
Data Visualization
100 100%
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare nbviewer.org and Deepnote

nbviewer.org Reviews

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Deepnote Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
Deepnote is a cloud-based data science notebook platform comparable to Jupyter Notebooks but with a focus on real-time collaboration and editing. It lets users write and run code in several programming languages, as well as include text, equations, and visualizations in a single document.
Source: lakefs.io
7 best Colab alternatives in 2023
Deepnote is a real-time collaborative notebook. It offers features like real-time collaboration, version control, and smart autocomplete. It also provides direct integrations with popular data sources like GitHub, Google Drive, and BigQuery. Its modern, intuitive interface makes it a compelling choice for both beginners and experienced data scientists.
Source: deepnote.com
12 Best Jupyter Notebook Alternatives [2023] – Features, pros & cons, pricing
Deepnote is a cloud-based, data science notebook platform that is similar to Jupyter Notebooks, but with a focus on collaboration and real-time editing. It allows users to write and execute code in a variety of programming languages, as well as include text, equations, and visualizations in a single document. Deepnote also has a built-in code editor and supports a wide range...
Source: noteable.io
The Best ML Notebooks And Infrastructure Tools For Data Scientists
A Jupyter-notebook enabled platform, Deepnote boasts of many advanced features. Deepnote supports real-time collaboration to discuss and debug the code. The platform will soon have functions such as versioning, code review, and reproducibility. Deepnote has intelligent features to quickly browse the code, find patterns in your data, and autocomplete code. It can integrate...

Social recommendations and mentions

Based on our record, Deepnote should be more popular than nbviewer.org. It has been mentiond 34 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

nbviewer.org mentions (13)

  • Jupyter kernel for Logtalk
    Example notebooks are included in the repo and can be previewed using nbviewer:. Source: over 2 years ago
  • Is there a CodePen/OverLeaf equivalent for sharing and viewing Jupyter Notebooks/Labs
    Nbviewer (https://nbviewer.org/): very easy to use for smaller jupyter notebook that does not require heavy rendering. Source: over 2 years ago
  • Collaborative Jupyter Whiteboards
    Nbconvert renders everything exactly as it looks in your notebook app into a read-only HTML version and is what GitHub uses for notebooks. Interactive plots from Bokeh, Holoviews, etc can still work if you trust the JS, and since editing notebooks while showing them during a meeting usually doesn't go well, read-only is probably good enough (eager to hear feedback on this point though). The nice thing is that... Source: over 2 years ago
  • First data science project (visualization): What should I improve on?
    Just as a heads up, I used plotly to generate a lot of the charts, so you'll need to view it from an nbviewer like nbviewer.org. Source: about 3 years ago
  • Can someone please review my data visualisation notebook?
    I used a lot of plotly not knowing that Github wouldn't show it, so you'll need notebook viewer like nbviewer.org to see some of the charts. Source: about 3 years ago
View more

Deepnote mentions (34)

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What are some alternatives?

When comparing nbviewer.org and Deepnote, you can also consider the following products

Livebook - Automate code & data workflows with interactive Elixir notebooks

Saturn Cloud - ML in the cloud. Loved by Data Scientists, Control for IT. Advance your business's ML capabilities through the entire experiment tracking lifecycle. Available on multiple clouds: AWS, Azure, GCP, and OCI.

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

Apache Zeppelin - A web-based notebook that enables interactive data analytics.

nteract - nteract is a desktop application that allows you to develop rich documents that contain prose...

Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.