🆚 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 #9
Site Search › Rank #23
JavaScript Libraries › Rank #201

Popularity

Determined by the number of sites using each technology.

The Lunr site search software is 3 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 Germany, the United States, and the United Kingdom, while Meilisearch is more popular in France, Portugal, and the Netherlands.
Germany
United States
France
Portugal
United Kingdom
Netherlands
Italy
Belgium
Spain
Canada

Awards

Popularity by domain category

Determined by the number of sites in each category.

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

Top sites

Top-ranked sites that use these technologies.

Name
Rank
#14,216
#15,564
#17,536
View more ➝
Name
Rank
#8,769
#9,670
#10,505
View more ➝

See also

🗃️ About This Data