D3.js vs Bokeh

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

D3.js is a Development solution with tags like javascript, data-binding, svg, graphs, charts.

It boasts features such as Data-Driven DOM Manipulation, Powerful Visualization Components, Animated Transitions, Highly Customizable and Flexible, Wide Browser Support and pros including 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.

On the other hand, Bokeh is a Development product tagged with python, data-visualization, interactive, graphics, web-browser.

Its standout features include Interactive data visualization, Supports streaming data, Python library, Targets modern web browsers, Elegant and concise graphics, High-performance interactivity, Can handle large datasets, and it shines with pros like 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.

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

Product Overview

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.

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.

Key Features Comparison

D3.js Features

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

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

Pros & Cons Analysis

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

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

Pricing Comparison

D3.js

• Open Source

Bokeh

• Open Source