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Bokeh vs Plotly: What are the differences?


Bokeh and Plotly are both interactive data visualization libraries that are commonly used in web applications. While they share some similarities, there are several key differences between the two.

  1. Backend Infrastructure: The major difference between Bokeh and Plotly lies in their backend infrastructure. Bokeh is a server-based library that generates JavaScript in the client-side browser to create interactive visualizations. On the other hand, Plotly is API-based and can be used with different programming languages to generate visualizations.

  2. Ease of Use: Bokeh provides a simplified and concise API that allows users to create visualizations with minimal code. It emphasizes ease of use and offers a wide range of pre-built plot types. Plotly, on the other hand, has a slightly steeper learning curve and requires a deeper understanding of the API and its different components.

  3. Interactivity: Bokeh is primarily designed for creating interactive visualizations, with support for interactivity such as hover tooltips, zooming, panning, and selection tools. Plotly, on the other hand, offers a more extensive set of interactivity options, including linked brushing, animations, and even 3D plotting capabilities.

  4. Offline vs. Online Usage: Bokeh supports both offline and online usage, meaning that you can generate visualizations without internet connectivity. Plotly, on the other hand, is built to work primarily in an online environment and requires an internet connection to retrieve data and create visualizations.

  5. Community and Documentation: Bokeh has a growing community of users and developers, and it provides comprehensive documentation and examples to help users get started. Plotly, on the other hand, has a larger and more active community, with extensive documentation and a wide range of user-contributed examples and tutorials.

  6. Cost and Licensing: Bokeh is an open-source library released under the BSD-3-Clause license, making it free to use and distribute. Plotly offers both open-source and commercial versions, with additional features available in the commercial version for enterprise users.

In Summary, Bokeh and Plotly are both powerful tools for creating interactive visualizations, but they differ in terms of their backend infrastructure, ease of use, interactivity options, offline/online usage, community support, and licensing.

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Pros of Bokeh
Pros of Plotly.js
  • 12
    Beautiful Interactive charts in seconds
  • 16
    Bindings to popular languages like Python, Node, R, etc
  • 10
    Integrated zoom and filter-out tools in charts and maps
  • 9
    Great support for complex and multiple axes
  • 8
    Powerful out-of-the-box featureset
  • 6
    Beautiful visualizations
  • 4
    Active user base
  • 4
    Impressive support for webgl 3D charts
  • 3
    Charts are easy to share with a cloud account
  • 3
    Webgl chart types are extremely performant
  • 2
    Interactive charts
  • 2
    Easy to use online editor for creating plotly.js charts
  • 2
    Publication quality image export

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Cons of Bokeh
Cons of Plotly.js
    Be the first to leave a con
    • 18
      Terrible document

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    What is Bokeh?

    Bokeh is an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics, and affords high-performance interactivity over large or streaming datasets.

    What is Plotly.js?

    It is a standalone Javascript data visualization library, and it also powers the Python and R modules named plotly in those respective ecosystems (referred to as and Plotly.R). It can be used to produce dozens of chart types and visualizations, including statistical charts, 3D graphs, scientific charts, SVG and tile maps, financial charts and more.

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    What companies use Bokeh?
    What companies use Plotly.js?
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    What tools integrate with Bokeh?
    What tools integrate with Plotly.js?

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    What are some alternatives to Bokeh and Plotly.js?
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    Dash is an API Documentation Browser and Code Snippet Manager. Dash stores snippets of code and instantly searches offline documentation sets for 150+ APIs. You can even generate your own docsets or request docsets to be included.
    It is a JavaScript library for manipulating documents based on data. Emphasises on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework.
    Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.
    It is an open source R package that provides an elegant and powerful web framework for building web applications using R. It helps you turn your analyses into interactive web applications without requiring HTML, CSS, or JavaScript knowledge.
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