🆚 D3.js vs. Morris.js

Type

JavaScript library
Charting library

About

D3.js is an open-source, low-level JavaScript toolbox for data visualization.

It supports loading data from CSV, JSON, and GeoJSON formats, provides scale functions for mapping data values to visual properties, includes layouts such as force-directed graphs, treemaps, and packed circles, and offers transitions, animations, and interaction tools like dragging, zooming, and panning.

Morris.js is an open-source JavaScript charting library for drawing simple line, bar, area, and donut charts with minimal configuration.

It renders charts through SVG using the Raphael and jQuery, and supports animated transitions, automatic resizing, hover tooltips, time-series data visualization, and customizable labels and colors.

Headquarters

San Francisco, California, United States

Website

Pricing

Free ✔️ Open source
Free ✔️ Open source

Categories

JavaScript Libraries › Rank #168
Charting › Rank #3
Charting › Rank #7

Popularity

Determined by the number of sites using each technology.

The D3.js JavaScript library is 2 times more popular than Morris.js.
Total websites

Market share

Charting

Popularity by country

Determined by the number of sites detected from each country.

D3.js is more popular in the United States, the United Kingdom, and Germany, while Morris.js is more popular in Australia, Iran, and South Africa.
United States
United Kingdom
Germany
France
India
Spain
Korea
Italy
Canada
Brazil

Awards

Popularity by domain category

Determined by the number of sites in each category.

D3.js is more popular among sites focused on business, education and reference, and marketing and merchandising, while Morris.js is more commonly used on sports, general news, and entertainment sites.
Business
Education/Reference
Marketing/Merchandising
Online Shopping
Travel
Internet Services
Sports
General News
Finance/Banking
Blogs/Wiki

Top sites

Top-ranked sites that use these technologies.

Name
Rank
#1,738
View more ➝
Name
Rank
xhsocial.com
#193
#1,353
View more ➝

See also

🗃️ About This Data