Streamlit vs Dash by Plotly

Struggling to choose between Streamlit and Dash by Plotly? Both products offer unique advantages, making it a tough decision.

Streamlit is a Ai Tools & Services solution with tags like python, web-app, dashboard.

It boasts features such as Quickly create web apps and dashboards in Python, Interactive widgets for user input, Support for major Python data science libraries, Real-time updates as code changes, Open-source and free and pros including Very fast and easy to build apps, No need to know frontend web dev, Great for data science workflows, Active community support.

On the other hand, Dash by Plotly is a Development product tagged with python, plotly, dashboard, visualization, analytics.

Its standout features include Interactive data visualization, Built on top of Plotly.js, React, and Flask, Supports many chart types like scatter plots, histograms, box plots, heatmaps, etc, Linked views for cross-filtering, Supports callbacks for dynamic updates and interactions, Layouts with CSS grid and flexbox, Authentication and role-based access control, Works with Pandas DataFrames, and it shines with pros like Open-source and free to use, Great for building analytical web apps quickly, Large library of customizable visualizations, Python-based, so easy for Python developers, Active community support.

Feature	Streamlit	Dash by Plotly
Overall Score	N/A	N/A
Primary Category	Ai Tools & Services	Development

Product Overview

Streamlit

Description: Streamlit is an open-source Python library for building web apps and dashboards quickly and easily. It allows you to create interactive data apps in Python without needing to know any JavaScript or HTML.

Dash by Plotly

Description: Dash by Plotly is an open-source Python framework for building analytical web applications. It makes it easy to build reactive, customizable dashboards by leveraging Flask, Plotly.js, and React.js.

Key Features Comparison

Streamlit Features

• Quickly create web apps and dashboards in Python
• Interactive widgets for user input
• Support for major Python data science libraries
• Real-time updates as code changes
• Open-source and free

Dash by Plotly Features

• Interactive data visualization
• Built on top of Plotly.js, React, and Flask
• Supports many chart types like scatter plots, histograms, box plots, heatmaps, etc
• Linked views for cross-filtering
• Supports callbacks for dynamic updates and interactions
• Layouts with CSS grid and flexbox
• Authentication and role-based access control
• Works with Pandas DataFrames

Pros & Cons Analysis

Streamlit

Pros

• Very fast and easy to build apps
• No need to know frontend web dev
• Great for data science workflows
• Active community support

Cons

• Limited customization compared to full web frameworks
• Hosting and deployment requires setup
• Less flexibility than JavaScript-based tools

Dash by Plotly

Pros

• Open-source and free to use
• Great for building analytical web apps quickly
• Large library of customizable visualizations
• Python-based, so easy for Python developers
• Active community support

Cons

• Steeper learning curve than some other BI tools
• Advanced customization requires knowledge of React
• Hosting and deployment may require DevOps skills
• Not as feature-rich as commercial BI platforms

Pricing Comparison

Streamlit

• Open Source

Dash by Plotly

• Open Source
• Freemium