Bokeh vs D3.js

Struggling to choose between Bokeh and D3.js? Both products offer unique advantages, making it a tough decision.

Bokeh is a Development solution with tags like python, data-visualization, interactive, graphics, web-browser.

It boasts features such as Interactive data visualization, Supports streaming data, Python library, Targets modern web browsers, Elegant and concise graphics, High-performance interactivity, Can handle large datasets and pros including Very flexible and customizable visualizations, Integrates well with other Python data tools like NumPy and Pandas, Open source and free, Good performance even with large datasets, Nice web-based interface for sharing visualizations.

On the other hand, D3.js is a Development product tagged with javascript, data-binding, svg, graphs, charts.

Its standout features include Data-Driven DOM Manipulation, Powerful Visualization Components, Animated Transitions, Highly Customizable and Flexible, Wide Browser Support, and it shines with pros like Open source and free, Large and active community support, Integrates well with other JS libraries, High performance with canvas rendering, Supports large datasets and real-time updates.

Feature	Bokeh	D3.js
Overall Score	N/A	N/A
Primary Category	Development	Development

Product Overview

Bokeh

Description: Bokeh is an interactive data visualization library for Python that targets modern web browsers for presentation. It offers elegant, concise construction of versatile graphics, and affords high-performance interactivity over large or streaming datasets.

D3.js

Description: D3.js is a JavaScript library for visualizing data with HTML, SVG, and CSS. It allows developers to bind arbitrary data to DOM elements and apply data-driven transformations to the document. Common uses are for creating interactive graphs, charts, maps, and data visualizations.

Key Features Comparison

Bokeh Features

• Interactive data visualization
• Supports streaming data
• Python library
• Targets modern web browsers
• Elegant and concise graphics
• High-performance interactivity
• Can handle large datasets

D3.js Features

• Data-Driven DOM Manipulation
• Powerful Visualization Components
• Animated Transitions
• Highly Customizable and Flexible
• Wide Browser Support

Pros & Cons Analysis

Bokeh

Pros

• Very flexible and customizable visualizations
• Integrates well with other Python data tools like NumPy and Pandas
• Open source and free
• Good performance even with large datasets
• Nice web-based interface for sharing visualizations

Cons

• Steeper learning curve than some visualization libraries
• Visualizations can be more complex to build
• Limited built-in statistical analysis features
• Requires knowledge of Python and web development
• Not as simple as drag-and-drop visualization builders

D3.js

Pros

• Open source and free
• Large and active community support
• Integrates well with other JS libraries
• High performance with canvas rendering
• Supports large datasets and real-time updates

Cons

• Steep learning curve
• Complex documentation
• Requires knowledge of SVG
• Not optimized for mobile platforms
• Version 3.0 has breaking changes from 2.0

Pricing Comparison

Bokeh

• Open Source

D3.js

• Open Source