StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. Business Tools
  3. UI Components
  4. Charting Libraries
  5. C3.js vs D3.js vs Plotly

C3.js vs D3.js vs Plotly

OverviewDecisionsComparisonAlternatives

Overview

D3.js
D3.js
Stacks2.0K
Followers1.7K
Votes653
GitHub Stars111.7K
Forks22.9K
C3.js
C3.js
Stacks398
Followers163
Votes4
Plotly.js
Plotly.js
Stacks399
Followers694
Votes69
GitHub Stars17.9K
Forks1.9K

C3.js vs D3.js vs Plotly: What are the differences?

C3.js, D3.js, and Plotly are popular JavaScript libraries used for data visualization on websites. Below are the key differences between these libraries:

1. **Learning Curve**: D3.js is considered to have a steep learning curve due to its low-level API that requires deep understanding of SVG, CSS, and JavaScript. C3.js, on the other hand, provides a higher-level API that simplifies the process of creating charts, making it easier for beginners. Plotly focuses on offering an intuitive interface and comprehensive documentation, making it user-friendly for users of all levels.

2. **Customization**: D3.js allows deep customization of every aspect of a chart, giving developers complete control over the visualizations. C3.js offers a simpler interface with predefined chart types and styles, limiting customization to some extent. Plotly provides a balance between customization and ease of use by offering various customization options through its interface.

3. **Interactivity**: D3.js provides extensive support for adding interactive elements to charts, allowing users to interact with data points and visuals in real-time. C3.js includes basic interactive features by default, such as tooltips and zooming, making it suitable for simple interactions. Plotly shines in interactivity by offering a wide range of interactive features and widgets for enhancing user engagement and data exploration.

4. **Community and Support**: D3.js has a large and active community that contributes to tutorials, examples, and plugins, providing comprehensive support for developers. C3.js has a growing community but may have fewer resources compared to D3.js. Plotly, being a commercial product, offers dedicated customer support and documentation, making it a reliable choice for businesses and professionals.

5. **Rendering Performance**: D3.js excels in rendering performance, as it directly manipulates the DOM for efficient updates and transitions, suitable for handling large datasets. C3.js abstracts the rendering process, which may have overhead compared to D3.js when dealing with complex visualizations. Plotly's rendering performance is optimized for web and mobile platforms, ensuring smooth user experience across devices.

6. **Integration and Compatibility**: D3.js can be seamlessly integrated with other JavaScript frameworks and libraries due to its flexibility, making it a preferred choice for developers working on complex web applications. C3.js is built on top of D3.js and provides easier integration with existing web projects that have less customization requirements. Plotly offers APIs for integrating its visualizations with various platforms, making it versatile for different development environments.

In Summary, the key differences between C3.js, D3.js, and Plotly lie in their learning curve, customization options, interactivity features, community support, rendering performance, and integration capabilities.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Advice on D3.js, C3.js, Plotly.js

Steve
Steve

Lead Software Tools Engineer at Leonardo UK

Oct 30, 2020

Review

I would specifically recommend basing your application on Pandas which will handle the vast majority of the work for you. You will be amazed at what you will be able to get done with only a few lines of code.

Pandas can load the data from either Excel xslx files or csv files (and a lot of other places)

If you structure your code well you can have a cross platform command line program, a GUI desktop program, a Jupyter Notebook and a web service all with the vast majority of the code in common.

A jupyter notebook is a great place to start developing your code and may be all that you need.

Some plug-ins & resources that can help:

  • pandas-summary (for a rapid overview of the data): https://github.com/mouradmourafiq/pandas-summary
  • pandasgui (for exploring what you would like to do): https://github.com/adamerose/pandasgui
  • Pandas-Bokeh (plotting): https://github.com/PatrikHlobil/Pandas-Bokeh
  • plot.ly (plotting): https://plotly.com/python/pandas-backend/
  • wxPython (for a desktop GUI): https://wxpython.org/
8.84k views8.84k
Comments
Ayaskant
Ayaskant

SSE-II at Akamai

Oct 25, 2019

Needs advice

I want to get suggestions on these 2 open source js libraries (D3.js & echarts) that help in creating charts or graphs on the UI. Which one will be better for bar graphs. Which is easy to learn and start with? Which provides better features and community support?

My requirements are 1 - Plot data in X-Y axis graph where x-axis will present time till seconds level and Y-Axis will present the data corresponding to that time.

2 - Zoom-in and zoom out feature.

56.1k views56.1k
Comments
Sudhan
Sudhan

Dec 23, 2019

Needs advice

I'm developing angular 8 application, I need to create a dynamic, custom charts based on the data, Charts options will be configured with a user input form. at any time users can edit and modify the chart options. even I dont know how many charts I have to create everything is dynamic. ( based on the user configuration chart counts will vary ). I need some suggestions on which chart will give these kinds of flexible options.

42.8k views42.8k
Comments

Detailed Comparison

D3.js
D3.js
C3.js
C3.js
Plotly.js
Plotly.js

It is a JavaScript library for manipulating documents based on data. Emphasises on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework.

c3 is a D3-based reusable chart library that enables deeper integration of charts into web applications.

It is a standalone Javascript data visualization library, and it also powers the Python and R modules named plotly in those respective ecosystems (referred to as Plotly.py and Plotly.R). It can be used to produce dozens of chart types and visualizations, including statistical charts, 3D graphs, scientific charts, SVG and tile maps, financial charts and more.

Declarative Approach for Individual Nodes Manipulation; Functions Factory; Web Standards; Built-in ELement Inspector to Debug; Uses SVG, Canvas, and HTML; Data-driven approach to DOM Manipulation; Voronoi Diagrams; Maps and topo.
Comfortable - C3 makes it easy to generate D3-based charts by wrapping the code required to construct the entire chart. We don't need to write D3 code any more.;Customizable - C3 gives some classes to each element when generating, so you can define a custom style by the class and it's possible to extend the structure directly by D3.;Controllable - C3 provides a variety of APIs and callbacks to access the state of the chart. By using them, you can update the chart even if after it's rendered.
Feature parity with MATLAB/matplotlib graphing; Online chart editor; Fully interactive (hover, zoom, pan); SVG and WebGL backends; Publication-quality image export
Statistics
GitHub Stars
111.7K
GitHub Stars
-
GitHub Stars
17.9K
GitHub Forks
22.9K
GitHub Forks
-
GitHub Forks
1.9K
Stacks
2.0K
Stacks
398
Stacks
399
Followers
1.7K
Followers
163
Followers
694
Votes
653
Votes
4
Votes
69
Pros & Cons
Pros
  • 195
    Beautiful visualizations
  • 103
    Svg
  • 92
    Data-driven
  • 81
    Large set of examples
  • 61
    Data-driven documents
Cons
  • 11
    Beginners cant understand at all
  • 6
    Complex syntax
Pros
  • 2
    Easy to use
  • 2
    Reusable charts
Cons
  • 1
    Dependent on D3.js which is not lightweight
Pros
  • 16
    Bindings to popular languages like Python, Node, R, etc
  • 10
    Integrated zoom and filter-out tools in charts and maps
  • 9
    Great support for complex and multiple axes
  • 8
    Powerful out-of-the-box featureset
  • 6
    Beautiful visualizations
Cons
  • 18
    Terrible document
Integrations
JavaScript
JavaScript
React Native
React Native
AngularJS
AngularJS
React
React
Bootstrap
Bootstrap
No integrations available
Python
Python
React
React
MATLAB
MATLAB
Jupyter
Jupyter
Julia
Julia

What are some alternatives to D3.js, C3.js, Plotly.js?

Highcharts

Highcharts

Highcharts currently supports line, spline, area, areaspline, column, bar, pie, scatter, angular gauges, arearange, areasplinerange, columnrange, bubble, box plot, error bars, funnel, waterfall and polar chart types.

Chart.js

Chart.js

Visualize your data in 6 different ways. Each of them animated, with a load of customisation options and interactivity extensions.

Recharts

Recharts

Quickly build your charts with decoupled, reusable React components. Built on top of SVG elements with a lightweight dependency on D3 submodules.

ECharts

ECharts

It is an open source visualization library implemented in JavaScript, runs smoothly on PCs and mobile devices, and is compatible with most current browsers.

ZingChart

ZingChart

The most feature-rich, fully customizable JavaScript charting library available used by start-ups and the Fortune 100 alike.

amCharts

amCharts

amCharts is an advanced charting library that will suit any data visualization need. Our charting solution include Column, Bar, Line, Area, Step, Step without risers, Smoothed line, Candlestick, OHLC, Pie/Donut, Radar/ Polar, XY/Scatter/Bubble, Bullet, Funnel/Pyramid charts as well as Gauges.

CanvasJS

CanvasJS

Lightweight, Beautiful & Responsive Charts that make your dashboards fly even with millions of data points! Self-Hosted, Secure & Scalable charts that render across devices.

AnyChart

AnyChart

AnyChart is a flexible JavaScript (HTML5) based solution that allows you to create interactive and great looking charts. It is a cross-browser and cross-platform charting solution intended for everybody who deals with creation of dashboard, reporting, analytics, statistical, financial or any other data visualization solutions.

ApexCharts

ApexCharts

A modern JavaScript charting library to build interactive charts and visualizations with simple API.

Bokeh

Bokeh

Bokeh is an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics, and affords high-performance interactivity over large or streaming datasets.

Related Comparisons

Bootstrap
Materialize

Bootstrap vs Materialize

Laravel
Django

Django vs Laravel vs Node.js

Bootstrap
Foundation

Bootstrap vs Foundation vs Material UI

Node.js
Spring Boot

Node.js vs Spring-Boot

Liquibase
Flyway

Flyway vs Liquibase