Create an Atlas Vector Search Index

New in version 1.42.1.

You can create Atlas Vector Search indexes using MongoDB Compass. These indexes enable you to index vector data and other data types, which facilitates semantic searches on the indexed fields. Atlas Vector Search indexes support indexing vector data by identifying the most similar vectors. The index determines similarity by calculating the distance between the query vector and the vectors stored in the index.

About this Task

To create an Atlas Search index, your deployment must align with one of the following cases:

A deployment hosted on MongoDB Atlas and have an Atlas cluster tier of M10 or higher.
A local deployment that is set up using the Atlas CLI.

Additionally, your deployment must run MongoDB version 7.0 or later.

Steps

Open the index creation dialog

From the Indexes tab, click the Create button and then click Search Index.

Specify a name for the index

Select the Atlas Search Index type

Select Vector Search.

Provide the Atlas Vector Search Index configurations

You must provide all required fields for your vector search index configuration. You can modify the configurations later. For more information on required fields in vector search index configurations, see Atlas Vector Search Index Fields.

Click Create Search Index

Example

The following example definition uses the sample_mflix.embedded_movies collection and indexes the plot_embedding field to create an Atlas Vector Search index:

{
   "fields": [ {
      "type": "vector",
      "path": "plot_embedding",
      "numDimensions": 1536,
      "similarity": "euclidean"
   } ]
}

Results

To view the status of your created index, go to the Indexes tab and set the toggle at the top-right to Search Indexes.

The Status column indicates the status of the index. When the status is Ready, your index is ready to use.

For more information on search index statuses, see Atlas Search Index Statuses.

Learn More

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Atlas Search Index

Analyze Data Schema