Dash vs Shiny

Dash vs Shiny comparison

Trying to decide what Python analytics framework is the right one for your project? Hopefully this comparison of Dash vs Shiny will help you make an informed decision. 

Dash vs Shiny - TLDR


(h3) (Dash):

  • Pros: Dash allows a very customizable experience by using React under the hood. Dash easily supports interactive visualizations. There is a huge and active community willing to help out each other.
  • Cons: Dash is focused around its own visualization library, and may require some extended CSS and HTML knowledge for customization. As Dash also has an Enterprise version, some functionality is reserved for Enterprise only.
  • Use (Dash) if: You need a high level of customization to adhere to your use-case and may need enterprise features in the future.
  • Alternatives: Streamlit and Shiny


  • Pros: While still being relatively new for python, Shiny for R has been around for a long time, so that a lot of experiences on that could be put into Shiny for python. Sharing similar concepts should also help R users to migrate. The core of shiny is a reactive programming engine, trying to reduce the required computations as much as possible.
  • Cons: Shiny uses Bootstrap as its framework for layout and styling - this means you must have understood the concepts of Bootstrap in order to change the UI.
  • Use (Shiny) if: You don't have time for web development but want to expose your python code as fast as possible.
  • Alternatives: Dash. Panel.

Compatibility with Firebolt

You can use Firebolt with both Strealit and Dash in order to build your applications.

Include the Python SDK for Firebolt to your dependencies and analyze your data stored in Firebolt right away!

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