Master Fast Full‑Text Search with Meilisearch: A Hands‑On Docker Tutorial

Introduction

Meilisearch is a lightweight search engine that supports a RESTful search API and has already earned over 50k+star on GitHub. Its goal is to provide a fast and accurate search experience for every user.

Fast search: results in under 50 ms

Instant search: results appear as you type

Smart typo‑tolerance

Comprehensive language support, especially Chinese

Highly customizable indexing and search behavior

RESTful API support

SDKs for Java, JavaScript, Go, Python, etc.

Installation

Deploy Meilisearch with Docker for quick setup.

docker pull getmeili/meilisearch:v1.13

docker run -p 7700:7700 --name meilisearch \
  -e MEILI_ENV='development' \
  -v /mydata/meiliData:/meili_data \
  -d getmeili/meilisearch:v1.13

After the container starts, access the Mini Dashboard at http://localhost:7700.

Usage

Index Operations

In Meilisearch, an index is a collection of documents, similar to a table in MySQL.

Download the official demo dataset from the Meilisearch documentation.

Upload the data to a server and import it with curl.

Import documents via curl:

curl \
  -X POST '{{MEILISEARCH_URL}}/indexes/movies/documents?primaryKey=id' \
  -H 'Content-Type: application/json' \
  --data-binary @movies.json

Search in the Mini Dashboard, e.g., type Transformers.

List all indexes:

curl \
  -X GET '{{MEILISEARCH_URL}}/indexes'

Delete an index:

curl \
  -X DELETE '{{MEILISEARCH_URL}}/indexes/movies'

Settings Operations

Settings are a JSON object that defines search behavior, similar to a table schema.

Query current settings:

curl \
  -X GET '{{MEILISEARCH_URL}}/indexes/movies/settings'

Modify settings to make title and release_date sortable, and genres and release_date filterable:

curl \
  -X PATCH '{{MEILISEARCH_URL}}/indexes/movies/settings' \
  -H 'Content-Type: application/json' \
  --data-binary '{
    "sortableAttributes": ["title", "release_date"],
    "filterableAttributes": ["genres", "release_date"]
  }'

Document Operations

Add a document:

curl \
  -X POST '{{MEILISEARCH_URL}}/indexes/movies/documents' \
  -H 'Content-Type: application/json' \
  --data-binary '{
    "id": 1,
    "title": "Transformers Test",
    "overview": "Young teenager, Sam Witwicky ...",
    "genres": ["Adventure", "Science Fiction", "Action"],
    "poster": "https://image.tmdb.org/t/p/w500/6eehp9I54syN3x753XMqjKz8M3F.jpg",
    "release_date": 1182902400
  }'

Retrieve a document:

curl \
  -X GET '{{MEILISEARCH_URL}}/indexes/movies/documents/1'

Update a document:

curl \
  -X PUT '{{MEILISEARCH_URL}}/indexes/movies/documents' \
  -H 'Content-Type: application/json' \
  --data-binary '[{"id": 1, "title": "Transformers Update"}]'

Delete a document:

curl \
  -X DELETE '{{MEILISEARCH_URL}}/indexes/movies/documents/1'

Search

Simple search for "Transformers":

curl \
  -X POST '{{MEILISEARCH_URL}}/indexes/movies/search' \
  -H 'Content-Type: application/json' \
  --data-binary '{ "q": "Transformers" }'

Paginated search (first 5 results):

curl \
  -X POST '{{MEILISEARCH_URL}}/indexes/movies/search' \
  -H 'Content-Type: application/json' \
  --data-binary '{ "q": "Transformers", "offset": 0, "limit": 5 }'

Sorted search by release date descending:

curl \
  -X POST '{{MEILISEARCH_URL}}/indexes/movies/search' \
  -H 'Content-Type: application/json' \
  --data-binary '{ "q": "Transformers", "offset": 0, "limit": 5, "sort": ["release_date:desc"]}'

Filtered search for Action or Adventure genres:

curl \
  -X POST '{{MEILISEARCH_URL}}/indexes/movies/search' \
  -H 'Content-Type: application/json' \
  --data-binary '{ "q": "Transformers", "offset": 0, "limit": 5, "sort": ["release_date:desc"], "filter": "genres = Action OR genres = Adventure"}'

Conclusion

Meilisearch delivers instant, low‑configuration full‑text search with speeds far exceeding many traditional solutions, making it a practical alternative to Elasticsearch for many projects.