Dash vs Streamlit compared

Dash vs Streamlit comparison

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

Dash vs Streamlit - TLDR


  • 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: Streamlit is well suited for fast prototyping. On top of being easy to understand and having a good documentation to get started, the real-time feedback when changing code allows for a fast turnaround. If you do not need a fully scalable application running with thousands of users, then putting a Streamlit application in production should not be a problem.
  • Cons: The biggest strength of fast prototyping is also the biggest weakness, as customization is limited. The look and feel can only be customized to a certain degree.
  • Use (Streamlit) if: you want a fast way of building applications and visualizations for your users, for example for a small internal data app.
  • Alternatives: Dash and Shiny

Firebolt Streamlit Example: https://github.com/spinscale/firebolt-streamlit-demo

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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