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Full-text search functionality in vCore-based Azure Cosmos DB for MongoDB provides powerful document searching capabilities beyond traditional query methods. This advanced search technique enables users to discover relevant content based on natural language processing, word variations, and contextual relevance—not just exact matches.
The integrated text search engine removes the need for external search services. This helps simplify your database architecture. It uses specialized text indexes to handle search operations efficiently. The system processes, tokenizes, and analyzes document content. As a result, your applications can quickly find documents that include specific keywords, phrases, or related terms.
Note
The full-text search in vCore-based Azure Cosmos DB for MongoDB uses a PostgreSQL-style TSVector index under the hood, with support for MongoDB’s $text operator.
Feature Support
| Feature | Support Level | Description | Sample Query |
|---|---|---|---|
| Tokenization | Supported | Breaks down text into individual tokens using TSVector | Not applicable |
| Stemming | Supported | Converts inflected words to their root form based on language analyzers | Not applicable |
| Language Support | Partially Supported | Supports common languages like Danish (da), Dutch (nl), English (en), Finnish (fi), French (fr), German (de), Hungarian (hu), Italian (it), Norwegian (nb), Portuguese (pt), Romanian (ro), Russian (ru), Spanish (es), Swedish (sv), Turkish (tr) etc. |
db.text_search.find({ "$text": { "$search": "leche", "$language": "es" } }) |
| Term-Based Search | Supported | Exact term search in indexed fields | db.movies.find({ "$text": { "$search": "surfer" } }) |
| Phrase Search | Partially Supported | Exact phrase match using quotes. Some compatibility issues exist. | db.text_search.find({ "$text": { "$search": "\"are cats\"" } }) |
| Prefix Query | Supported | Find terms starting with a pattern using regex | db.articles.find({ title: { $regex: /^data/i } }) |
| Wildcard Search | Supported | Match flexible patterns using regex + $text |
db.articles.find({ $and: [ { $text: { $search: "hello" } }, { title: { $regex: /.*world.*/i } } ] }) |
| Regex Search | Supported | Use regular expressions for flexible text pattern matching | db.articles.find({ title: { $regex: /^hello.*world$/i } }) |
| Boolean Operators | Supported | Use +, - to include/exclude terms |
db.text_search.find({ "$text": { "$search": "cafe +con" } }) |
| Multi-Match | Partially Supported | Multi-field query via combined index with weights | db.myColl.createIndex({ title: "text", genre: "text" }, { default_language: "english", weights: { title: 10, genre: 3 } }) |
| Faceted Search | Not Available | Filter search results by categories or tags (e.g., brand, color, price). Not supported natively in vCore text search. | Not applicable |
| Autocomplete & Boost | Not Available | Autocomplete (type-ahead suggestions) and query-time boosting of specific terms are not supported. Boosting can only be done at index level via field weights. | Not applicable |
| Custom Analyzers | Not Available | Custom tokenization or filtering not supported | Not applicable |
| Synonym Support | Not Available | No native support for synonyms | Not applicable |
| Fuzzy Search | Not Available | No typo-tolerant or fuzzy match support | Not applicable |
| Proximity Search | Not Available | Cannot search for terms within specific word distances | Not applicable |