MongoDB Text Indexes (original) (raw)

Last Updated : 5 May, 2026

MongoDB Text Indexes enable fast full-text search on string fields, allowing efficient querying of words and phrases across large text datasets, especially in unstructured or semi-structured data.

• Optimizes full-text search on text-based fields.
• Supports searching words and phrases within strings.
• Improves query performance on large textual datasets.
• Useful for unstructured or semi-structured text data.

Create a Text Index in MongoDB

A text index is created using createIndex() on one or more string fields, enabling full-text search across multiple fields and allowing compound text indexes with non-text fields.

**Syntax:

db.collectionName.createIndex( { field: "text" } )

Example of Creating a Text Index

In this example, we will be working with

• **Database: gfg
• **Collection: studentsposts
• **Documents: Two documents

Create a text index on "title" field of "studentsposts" collection in order to search inside the collection.

**Query:

db.studentsposts.createIndex({title: "text"})

**Output:

Now, we will see how to search using Text Index:

**Query:

db.studentsposts.find({$text:{$search: "mongodb"}})

**Output:

• Matches documents containing “mongodb” in text-indexed fields.
• Searches across title and tags (text index).
• Supports term variations (e.g., “mongodb learning”).
• Returns only documents matched by the text index.

Drop Text Index in MongoDB

Use db.collection.dropIndex() to remove a specific text index from a collection when it is no longer needed or needs to be recreated with different options.

**Syntax:

The syntax for MongoDB dropIndex method is:

db.collection.dropIndex("TextIndex")

Example of Drop Index in MongoDB

First, find the index of the field.

**Query:

db.studentsposts.getIndexes()

**Output:

Now, drop the text index using dropIndex() method.

**Query:

db.studentsposts.dropIndex("title_text")

Field Weights in Text Indexes

In MongoDB text indexes, field weights control the relevance score of documents by assigning higher importance to matches in specific fields during full-text search.

• Weights control how much each field contributes to the text search relevance score.
• MongoDB multiplies term matches by field weights to compute the final score.
• Default weight is 1 and can be configured during createIndex().

**Example:

db.studentsposts.createIndex(
{ title: "text", tags: "text" },
{
weights: { title: 10, tags: 5 },
name: "TextIndex"
}
)

Here, the weight of the title and tags are 10 and 5 respectively.

Wildcard Text Index in MongoDB

A wildcard text index ($**) indexes all string fields in a collection, enabling full-text search across dynamic or unknown fields in unstructured data.

• Indexes every field that contains string data in the collection.
• Enables full-text search across unknown or dynamic fields.
• Useful for unstructured and ad-hoc search scenarios.
• Can be included as part of a compound index.

Example of Wildcard Index in MongoDB

Create the text indexes using a wildcard specifier.

db.studentsposts.createIndex( { "$**": "text" } )

**Output:

Check all the indexes present in the studentsposts collection.

Limitations of MongoDB Text Indexes

While text indexes are powerful, there are some important limitations to be aware of:

• **Only One Text Index per Collection: MongoDB allows only one text index per collection.
• **Limited Use of hint(): The $text query automatically uses the text index and cannot be forced to use another index.
• **Sorting Limitation: Text search results are typically sorted using textScore, not normal field sorting.
• **Restrictions in Compound Text Index: Cannot include multi-key or geospatial index fields.

Important Points About MongoDB Text Indexes

MongoDB Text Indexes provide efficient full-text search capabilities with support for weighted fields, multi-field indexing, and easy index management.

• Enables fast full-text search on textual data stored in collections.
• Created using createIndex() by specifying one or more fields as "text".
• Supports field weights to control relevance scoring in search results.
• Allows indexing multiple fields and combining text indexes with other index keys.
• Can be removed using dropIndex() by specifying the index name.