EJSCharts vs Bokeh

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

EJSCharts is a Development solution with tags like charts, data-visualization, graphing.

It boasts features such as Supports various chart types like line, bar, pie, scatter, radar, candlestick etc, Interactive and customizable charts, Animated transitions and interactions, Touch support for mobile devices, Canvas rendering for better performance, Client-side data processing, Export charts as images, Open source and free and pros including Easy to use API, Good documentation, Lightweight and fast, Many customization options, Supports large datasets, Works across devices and browsers.

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	EJSCharts	Bokeh
Overall Score	N/A	N/A
Primary Category	Development	Development

Product Overview

EJSCharts

Description: EJSCharts is a feature-rich JavaScript charting library that allows you to create interactive charts and graphs in the browser. It has support for a wide variety of chart types including line, bar, pie, scatter, radar, candlestick and more.

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

EJSCharts Features

• Supports various chart types like line, bar, pie, scatter, radar, candlestick etc
• Interactive and customizable charts
• Animated transitions and interactions
• Touch support for mobile devices
• Canvas rendering for better performance
• Client-side data processing
• Export charts as images
• Open source and free

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

EJSCharts

Pros

• Easy to use API
• Good documentation
• Lightweight and fast
• Many customization options
• Supports large datasets
• Works across devices and browsers

Cons

• Less chart types than some competitors
• Lacks some advanced features like 3D charts
• Relies on Canvas, so no SVG output
• Requires learning JavaScript to use

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

EJSCharts

• Open Source

Bokeh

• Open Source