Bokeh vs C3.js

Struggling to choose between Bokeh and C3.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, C3.js is a Development product tagged with javascript, d3js, charts, data-visualization.

Its standout features include Supports common chart types like line, bar, pie, scatter, stacked, etc, Built on top of D3.js, Simplifies D3 code, Good documentation and examples, Open source and free, and it shines with pros like Easy to get started with basic charts, Large number of chart types supported, Interactive and customizable, Lightweight, Good performance.

To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.

Bokeh

Bokeh

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.

Categories:
Development Data Visualization
python data-visualization interactive graphics web-browser

Bokeh Features

  1. Interactive data visualization
  2. Supports streaming data
  3. Python library
  4. Targets modern web browsers
  5. Elegant and concise graphics
  6. High-performance interactivity
  7. Can handle large datasets

Pricing

  • Open Source

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

C3.js

C3.js

C3.js is an open-source JavaScript library for creating interactive data visualizations and charts using HTML, CSS, and SVG. It's a wrapper for D3.js that simplifies common chart types like line, bar, pie, scatter, stacked, etc. making them easier to generate.

Categories:
Development Data Visualization
javascript d3js charts data-visualization

C3.js Features

  1. Supports common chart types like line, bar, pie, scatter, stacked, etc
  2. Built on top of D3.js
  3. Simplifies D3 code
  4. Good documentation and examples
  5. Open source and free

Pricing

  • Open Source

Pros

Easy to get started with basic charts

Large number of chart types supported

Interactive and customizable

Lightweight

Good performance

Cons

Less flexible than pure D3.js

Limited customization for complex visualizations

Smaller community than D3.js

Only supports SVG, not Canvas