🆚 Lunr vs. Meilisearch

Type

Site search software
Site search software

About

Lunr.js is a small full-text search JavaScript library for use in the browser.

Meilisearch is an open-source AI-powered hybrid search engine for applications and websites that combines keyword-based and vector-based search to retrieve results using both lexical matching and semantic similarity.

It provides a REST API and client libraries for multiple programming languages, supports full-text search with typo tolerance, synonyms, faceted filtering, customizable sorting, and vector embeddings for semantic search.

Headquarters

Cape Town, South Africa
Paris, France

Website

Pricing

Free ✔️ Open source
Free version ✔️ Self-managed, open source
Cloud
Build
(100K documents, 50K searches)
$30+/month
Pro
(1M documents, 250K searches)
$300+/month

Categories

Site Search › Rank #17
Site Search › Rank #24
JavaScript Libraries › Rank #229

Popularity

Determined by the number of sites using each technology.

The Lunr site search software is 1.4 times more popular than Meilisearch.
Total websites

Market share

Site Search

Popularity by country

Determined by the number of sites detected from each country.

Lunr is more popular in the United States, Germany, and the United Kingdom, while Meilisearch is more popular in France, Portugal, and Belgium.
United States
Germany
France
Portugal
United Kingdom
Belgium
Netherlands
Canada
Italy
Australia

Awards

Popularity by domain category

Determined by the number of sites in each category.

Lunr is more popular among sites focused on business, blogs and wiki, and software and hardware, while Meilisearch is more commonly used on online shopping, marketing and merchandising, and Internet services sites.
Business
Online Shopping
Blogs/Wiki
Marketing/Merchandising
Software/Hardware
Internet Services
Education/Reference
Fashion/Beauty
Travel
Entertainment

Top sites

Top-ranked sites that use these technologies.

Name
Rank
#14,216
#15,564
#17,536
View more ➝
Name
Rank
#9,670
#21,752
#22,553
View more ➝

See also

🗃️ About This Data