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Bokeh vs Tableau

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Bokeh
95
182
+ 1
12
Tableau
1.3K
1.3K
+ 1
8
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Bokeh vs Tableau: What are the differences?

<Write Introduction here>

  1. Integration with Python Programming Language: Bokeh is a Python library that provides interactive visualization capabilities for the web, making it ideal for users familiar with Python for data analysis. On the other hand, Tableau is a standalone software that offers a user-friendly interface for creating visually appealing data visualizations without the need for programming skills.

  2. Open Source vs. Proprietary Software: Bokeh is an open-source library, allowing users to freely access and modify the source code to cater to their specific needs. Tableau, on the other hand, is proprietary software that requires a license for full functionality, limiting the flexibility and customization options available to users.

  3. Scalability and Performance: Bokeh is known for its scalability, enabling users to create complex and interactive visualizations efficiently. Conversely, Tableau may face performance issues when dealing with large datasets or complex visualizations, impacting the overall user experience.

  4. Community Support and Ecosystem: Bokeh benefits from a robust community of developers and contributors who continually enhance its features and provide support through forums and documentation. While Tableau also has a community of users, the level of customizability and extensibility offered by Bokeh surpasses that of Tableau.

  5. Mapping Capabilities: Bokeh excels in geospatial visualization with its high-quality mapping capabilities, allowing users to create interactive maps with ease. Tableau, while capable of creating maps, may lack the advanced geospatial features and customization options available in Bokeh.

  6. Real-time Data Streaming: Bokeh provides support for real-time data streaming and updating visualizations dynamically, making it suitable for applications that require real-time data analysis. In contrast, Tableau may require manual data refreshes or lack the seamless integration for real-time data visualization.

In Summary, Bokeh and Tableau differ in their integration with Python, open-source vs. proprietary nature, scalability, community support, mapping capabilities, and real-time data streaming features.

Decisions about Bokeh and Tableau
Wei Wei
CTO at Flux · | 1 upvote · 219.6K views
Chose
ModeMode
over
LookerLookerTableauTableau
at

Very easy-to-use UI. Good way to make data available inside the company for analysis.

Has some built-in visualizations and can be easily integrated with other JS visualization libraries such as D3.

Can be embedded into product to provide reporting functions.

Support team are helpful.

The only complain I have is lack of API support. Hard to track changes as codes and automate report deployment.

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Vojtech Kopal
Head of Data at Mews Systems · | 3 upvotes · 316.8K views
Chose
Power BIPower BI
over
LookerLookerTableauTableau
at

Power BI is really easy to start with. If you have just several Excel sheets or CSV files, or you build your first automated pipeline, it is actually quite intuitive to build your first reports.

And as we have kept growing, all the additional features and tools were just there within the Azure platform and/or Office 365.

Since we started building Mews, we have already passed several milestones in becoming start up, later also a scale up company and now getting ready to grow even further, and during all these phases Power BI was just the right tool for us.

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Pros of Bokeh
Pros of Tableau
  • 12
    Beautiful Interactive charts in seconds
  • 6
    Capable of visualising billions of rows
  • 1
    Intuitive and easy to learn
  • 1
    Responsive

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Cons of Bokeh
Cons of Tableau
    Be the first to leave a con
    • 3
      Very expensive for small companies

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    - No public GitHub repository available -

    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 Tableau?

    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.

    Need advice about which tool to choose?Ask the StackShare community!

    What companies use Bokeh?
    What companies use Tableau?
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    What tools integrate with Bokeh?
    What tools integrate with Tableau?

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    What are some alternatives to Bokeh and Tableau?
    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 Plotly.py 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.
    Matplotlib
    It is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. It can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application servers, and four graphical user interface toolkits.
    Dash
    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.
    D3.js
    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.
    Shiny
    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.
    See all alternatives

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