Elasticsearch vs Meilisearch: which one to choose for your project

Example Use Case: Building a Search Engine for a Blog

Let's consider a simple example of building a search engine for a blog using Elasticsearch. We'll create an index for our blog posts and perform a search query to retrieve relevant results.

// Create an index for our blog posts
curl -X PUT 'http://localhost:9200/blog_posts' -H 'Content-Type: application/json' -d '{
  "settings": {
    "number_of_shards": 1,
    "number_of_replicas": 0
  },
  "mappings": {
    "properties": {
      "title": {"type": "text"},
      "content": {"type": "text"}
    }
  }
}'

// Index a blog post
curl -X POST 'http://localhost:9200/blog_posts/_doc' -H 'Content-Type: application/json' -d '{
  "title": "Elasticsearch vs Meilisearch",
  "content": "In this article, we'll compare Elasticsearch and Meilisearch for building a search engine."
}'

// Perform a search query
curl -X GET 'http://localhost:9200/blog_posts/_search' -H 'Content-Type: application/json' -d '{
  "query": {
    "match": {
      "title": "Elasticsearch"
    }
  }
}'

Meilisearch: A Modern Alternative

Meilisearch is a modern, open-source search engine designed for building scalable and efficient search applications. It's built on top of the Rust programming language and provides a simple, RESTful API for interacting with the search engine.

Key Features of Meilisearch

• Full-text search**: Meilisearch supports advanced full-text search capabilities, including query analysis, tokenization, and stemming.
• Faceting**: Meilisearch allows you to perform faceting, which enables you to filter search results based on specific attributes.
• Ranking**: Meilisearch provides a ranking system, which enables you to prioritize search results based on relevance.
• Scalability**: Meilisearch is designed to scale horizontally, making it suitable for large-scale applications.

// Create an index for our products
curl -X POST 'http://localhost:7700/indexes' -H 'Content-Type: application/json' -d '{
  "name": "products",
  "fields": [
    {
      "name": "title",
      "type": "string"
    },
    {
      "name": "description",
      "type": "string"
    }
  ]
}'

// Index a product
curl -X POST 'http://localhost:7700/indexes/products/documents' -H 'Content-Type: application/json' -d '{
  "title": "Product 1",
  "description": "This is a product description."
}'

// Perform a search query
curl -X GET 'http://localhost:7700/indexes/products/search' -H 'Content-Type: application/json' -d '{
  "q": "product"
}'