Features - Meilisearch Documentation

Meilisearch indexes your content and makes it accessible to both humans and AI. Here’s everything it can do.

Search capabilities

Full-text search

Lightning-fast keyword search with typo tolerance and customizable relevancy.

Feature	Description
Sub-50ms responses	Fast search regardless of dataset size
Typo tolerance	Get relevant results even with spelling mistakes
Ranking rules	6 default rules plus custom ranking
Ranking score	Relevancy scores with optional detailed breakdown
Synonyms	Define equivalent terms for better recall
Stop words	Ignore common words like “the” or “and”
Distinct attribute	Deduplicate results by a specific field
Prefix search	Results update as users type
Matching strategy	Control how query terms are matched: `last`, `all`, or `frequency`
Phrase search	Use double quotes to search for an exact phrase
Negative search	Exclude terms from results using the minus operator
Placeholder search	Return all results when the query is empty

Querying and result formatting

Feature	Description
Highlighting	Emphasize query matches in results with customizable tags
Cropping	Return only the relevant portion of long text fields
Matches position	Get byte positions and lengths of matched terms
Search cutoff	Set a maximum time limit for search queries
Tokenization	Customize how queries are broken into tokens, with custom separators and dictionaries

AI-powered search

Semantic and hybrid search using vector embeddings for meaning-based results.

Feature	Description
Hybrid search	Combine keyword and semantic search
Embedders	OpenAI, Hugging Face, Cohere, Mistral, Voyage, Gemini, Cloudflare, Ollama, and custom REST
Similar documents	Find related content automatically
Image search	Search images with multimodal embeddings
Multi-embedder	Multiple embedding models on the same document
User-provided vectors	Bring your own pre-generated embeddings

Conversational search

Build chat interfaces powered by your search data with LLM integration.

Feature	Description
Chat completions	RAG-powered conversational search
LLM providers	OpenAI, Azure OpenAI, Mistral, Google Gemini, vLLM, and custom providers
Streaming responses	Stream chat responses in real time
Chat workspaces	Configure chat settings per index

Personalization

Feature	Description
User preference ranking	Re-rank results based on individual user preferences using AI embeddings
Real-time adaptation	Adjust results as user preferences evolve

Filtering and faceting

Refine search results with powerful filters and build faceted navigation.

Feature	Description
Filters	Filter by any attribute with complex expressions (AND/OR)
Facets	Build faceted navigation interfaces
Facet types	AND/OR operators, numeric, boolean, and date facets
Sorting	Sort results by any field
Geo search	Geo radius, bounding box, geo sorting, and distance calculation

Multi-search and federation

Query multiple indexes in a single request for complex search scenarios.

Feature	Description
Multi-search	Query multiple indexes at once
Federated search	Merge results from multiple sources with configurable weights

Scaling

Scale Meilisearch horizontally across multiple instances or optimize resource usage on a single node.

Feature	Description
Sharding	Distribute documents across multiple instances for horizontal scaling
Replication	Replicate data across multiple instances for high availability
Remote federation	Federate search across multiple Meilisearch instances
Memory mapping	Efficient memory usage through memory-mapped storage

Database

Document database

Feature	Description
Schemaless	Index documents without a predefined schema
Documents	Add, replace, update, and delete documents
Delete by filter	Delete documents matching a filter expression
Update by function	Partial updates to documents using functions
Searchable attributes	Configure which fields are searchable and their priority
Displayed attributes	Control which fields are returned in results
Filterable attributes	Define which fields can be used in filters
Sortable attributes	Define which fields can be used for sorting
Index swap	Swap indexes to perform updates without downtime

Vector database

Feature	Description
Similar documents	Find semantically similar documents using vector embeddings
Binary quantization	Compress vectors to save storage
DiskANN	Disk-based approximate nearest neighbors for large datasets
Auto embedding	Automatically generate embeddings without manual input

Platform features

Security

Protect your data with API keys and multi-tenant access control.

Feature	Description
API keys	Admin, search, and chat key types for different access levels
Tenant tokens	Secure multi-tenant applications with document-level access control
Search rules	Restrict which documents users can access

Tasks and monitoring

Monitor indexing operations and receive notifications.

Feature	Description
Task management	Track and manage async operations
Batches	Automatic task batching for efficient processing
Webhooks	Get notified when tasks complete
Diff indexing	Only index differences between datasets

Analytics (Cloud)

Track search behavior and optimize relevancy with built-in analytics.

Feature	Description
Search analytics	Monitor search patterns, no-result rates, and top queries
Click tracking	Track which results users engage with
Metrics reference	Click-through rate, conversion rate, average click position
Monitoring	Search latency, indexing latency, bandwidth, and API health

Pagination

Feature	Description
Pagination	Offset/limit and cursor-based pagination

Language support

Meilisearch provides optimized support for many languages:

Latin-based languages: English, French, Spanish, German, Italian, Portuguese, etc.
CJK: Chinese, Japanese, Korean with specialized tokenization
RTL languages: Hebrew, Arabic
Others: Thai, Greek, and more

See full language support →

Cloud features

These features are available exclusively on Meilisearch Cloud.

Feature	Description
Crawler	Crawl web pages with JS rendering, DocSearch mode, and schema extraction
Search preview	Visual search interface with filtering, sorting, and document CRUD
Teams	Organize projects and members into team workspaces
Enterprise SSO/SCIM	SAML 2.0 SSO and automated user provisioning
Autoscale disk	Automatically scale storage as data grows
Automatic backups	Scheduled backups for data safety
One-click upgrade	Upgrade Meilisearch version with a single click
Up to 99.999% SLA	Industry-leading service level agreement

Self-hosting

Feature	Description
Configuration	CLI flags and environment variables
Snapshots	Full binary copies for fast restoration
Dumps	Portable JSON exports for migration
Master key	Secure your instance with a master key

Integration options

Option	Description
REST API	Direct HTTP integration
Official SDKs	10+ language SDKs
Frameworks	Laravel, Rails, Strapi, Symfony

​Search capabilities

​Full-text search

​Querying and result formatting

​AI-powered search

​Conversational search

​Personalization

​Filtering and faceting

​Multi-search and federation

​Scaling

​Database

​Document database

​Vector database

​Platform features

​Security

​Tasks and monitoring

​Analytics (Cloud)

​Pagination

​Language support

​Cloud features

​Self-hosting

​Integration options