🆚 JSON-LD vs. Microformats

Type

Semantic markup technology
Semantic markup technology

About

JavaScript Object Notation for Linked Data (JSON-LD) is a lightweight linked data format used to embed structured data into web pages in a machine-readable form.

It is based on JSON and standardized by the W3C, uses context mapping to link data to the Schema.org vocabulary, allows embedding via script tags without affecting page markup, and supports graph-based structures for representing entities and their relationships.

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Microformats (μF) are a set of standardized HTML class names and attributes used to embed descriptive metadata within existing page content for entities such as people, events, reviews, and blog posts.

The original Microformats v1 specification defined formats such as hCard for people and organizations, hCalendar for events, hReview for reviews, hRecipe for recipes, and hProduct for commerce data, using conventional HTML class attributes.

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Headquarters

Cambridge, Massachusetts, United States
San Francisco, California, United States

Website

Categories

Semantic Markup › Rank #4
Semantic Markup › Rank #8

Popularity

Determined by the number of sites using each technology.

JSON-LD semantic markup technology is 11 times more popular than Microformats.
Total websites

Market share

Semantic Markup

Popularity by country

Determined by the number of sites detected from each country.

JSON-LD is more popular than Microformats in all countries.
United States
United Kingdom
Germany
France
Japan
Spain
Italy
Netherlands
Australia
India

Awards

Popularity by domain category

Determined by the number of sites in each category.

JSON-LD is more popular than Microformats in all market segments.
Business
Marketing/Merchandising
Online Shopping
Blogs/Wiki
Education/Reference
Internet Services
Travel
Entertainment
Health
General News

Top sites

Top-ranked sites that use these technologies.

Name
Rank
View more ➝
Name
Rank
ekstrabladet.dk
#557
desitales2.com
#865
desikahani2.net
#971
freesexkahani.com
#972
View more ➝

See also

🗃️ About This Data