Index Property: name

Supported index types

Option	3.6	4.0	5.0	8.0	Elastic Cluster
single field	Yes	Yes	Yes	Yes	Yes
compound	Yes	Yes	Yes	Yes	Yes
multi-key	Yes	Yes	Yes	Yes	Yes
text	No	No	Yes	Yes	No
geospatial	Yes	Yes	Yes	Yes	Yes
vector	No	No	Yes	Yes	No

Use the name option to provide an optional name for the index.

All examples use the following sample document:

{
  "productId": "PROD133726",
  "sku": "SKU24224",
  "name": "Basic Printer",
  "manufacturer": "The Manufacturer",
  "tags": [ "printer", "basic", "electronics", "business" ],
  "barcodes": [ "542364671", "886330670", "437445606" ],
  "reviews": [
    {
      "review_date": ISODate('2024-01-19T21:37:10.585Z'),
      ...
    }
  ],
  "material": "Polycarbonate",
  "color": "Space Gray",
  "supplier": {
    "supplierId": "SUP4",
    "location": {
      "type": "Point",
      "coordinates": [ -71.0589, 42.3601 ]
    }
  },
  "productEmbedding": [
    -0.019320633663838058,
    0.019672111388113596
  ],
  "lastUpdated": ISODate('2025-10-20T21:37:10.585Z')
}

Single field

db.collection.createIndex(
  {
    "productId": 1
  },
  {
    "name": "single_field_index"
  }
)

Compound

db.collection.createIndex(
  {
    "productId": 1,
    "manufacturer": 1
  },
  {
    "name": "compound_index"
  }
)

Multi-key

db.collection.createIndex(
  {
    "tags": 1
  },
  {
    "name": "multikey_index"
  }
)

Text

db.collection.createIndex(
  {
    "name": "text"
  },
  {
    "name": "text_index"
  }
)

Geospatial

db.collection.createIndex(
  {
    "supplier.location": "2dsphere"
  },
  {
    "name": "geospatial_index"
  }
)

Vector

db.runCommand({
  "createIndexes": "collection", 
  "indexes": [{
    "key": {
      "productEmbedding": "vector"
    },
    "name": "hnsw_index",
    "vectorOptions": {
      "type": "hnsw",
      "dimensions": 2,
      "similarity": "euclidean",
      "m": 16,
      "efConstruction": 64
    }
  }] 
})