Query data by using Azure Cosmos DB for MongoDB

  • 09/14/2024

APPLIES TO: MongoDB

The Azure Cosmos DB's API for MongoDB supports MongoDB queries.

This article covers the following tasks:

  • Querying data stored in your Azure Cosmos DB database using MongoDB shell

You can get started by using the examples in this article.

Sample document

The queries in this article use the following sample document.

{
  "id": "WakefieldFamily",
  "parents": [
      { "familyName": "Wakefield", "givenName": "Robin" },
      { "familyName": "Miller", "givenName": "Ben" }
  ],
  "children": [
      {
        "familyName": "Merriam", 
        "givenName": "Jesse", 
        "gender": "female", "grade": 1,
        "pets": [
            { "givenName": "Goofy" },
            { "givenName": "Shadow" }
        ]
      },
      { 
        "familyName": "Miller", 
         "givenName": "Lisa", 
         "gender": "female", 
         "grade": 8 }
  ],
  "address": { "state": "NY", "county": "Manhattan", "city": "NY" },
  "creationDate": 1431620462,
  "isRegistered": false
}

Example query 1

Given the sample family document, the following query returns the documents where the id field matches WakefieldFamily.

Query:

db.families.find({ id: "WakefieldFamily"})

Results:

{
    "_id": "ObjectId(\"58f65e1198f3a12c7090e68c\")",
    "id": "WakefieldFamily",
    "parents": [
      {
        "familyName": "Wakefield",
        "givenName": "Robin"
      },
      {
        "familyName": "Miller",
        "givenName": "Ben"
      }
    ],
    "children": [
      {
        "familyName": "Merriam",
        "givenName": "Jesse",
        "gender": "female",
        "grade": 1,
        "pets": [
          { "givenName": "Goofy" },
          { "givenName": "Shadow" }
        ]
      },
      {
        "familyName": "Miller",
        "givenName": "Lisa",
        "gender": "female",
        "grade": 8
      }
    ],
    "address": {
      "state": "NY",
      "county": "Manhattan",
      "city": "NY"
    },
    "creationDate": 1431620462,
    "isRegistered": false
}

Example query 2

The next query returns all the children in the family.

Query:

db.families.find( { id: "WakefieldFamily" }, { children: true } )

Results:

{
    "_id": "ObjectId("58f65e1198f3a12c7090e68c")",
    "children": [
      {
        "familyName": "Merriam",
        "givenName": "Jesse",
        "gender": "female",
        "grade": 1,
        "pets": [
          { "givenName": "Goofy" },
          { "givenName": "Shadow" }
        ]
      },
      {
        "familyName": "Miller",
        "givenName": "Lisa",
        "gender": "female",
        "grade": 8
      }
    ]
}

Example query 3

The next query returns all the families that are registered.

Query:

db.families.find( { "isRegistered" : true })

Results:

No document is returned.

Example query 4

The next query returns all the families that aren't registered.

Query:

db.families.find( { "isRegistered" : false })

Results:

{
    "_id": ObjectId("58f65e1198f3a12c7090e68c"),
    "id": "WakefieldFamily",
    "parents": [{
        "familyName": "Wakefield",
        "givenName": "Robin"
    }, {
        "familyName": "Miller",
        "givenName": "Ben"
    }],
    "children": [{
        "familyName": "Merriam",
        "givenName": "Jesse",
        "gender": "female",
        "grade": 1,
        "pets": [{
            "givenName": "Goofy"
        }, {
            "givenName": "Shadow"
        }]
    }, {
        "familyName": "Miller",
        "givenName": "Lisa",
        "gender": "female",
        "grade": 8
    }],
    "address": {
        "state": "NY",
        "county": "Manhattan",
        "city": "NY"
    },
    "creationDate": 1431620462,
    "isRegistered": false
}

Example query 5

The next query returns all the families that aren't registered and state is NY.

Query:

db.families.find( { "isRegistered" : false, "address.state" : "NY" })

Results:

{
    "_id": ObjectId("58f65e1198f3a12c7090e68c"),
    "id": "WakefieldFamily",
    "parents": [{
        "familyName": "Wakefield",
        "givenName": "Robin"
    }, {
        "familyName": "Miller",
        "givenName": "Ben"
    }],
    "children": [{
        "familyName": "Merriam",
        "givenName": "Jesse",
        "gender": "female",
        "grade": 1,
        "pets": [{
            "givenName": "Goofy"
        }, {
            "givenName": "Shadow"
        }]
    }, {
        "familyName": "Miller",
        "givenName": "Lisa",
        "gender": "female",
        "grade": 8
    }],
    "address": {
        "state": "NY",
        "county": "Manhattan",
        "city": "NY"
    },
    "creationDate": 1431620462,
    "isRegistered": false
}

Example query 6

The next query returns all the families where children grades are 8.

Query:

db.families.find( { children : { $elemMatch: { grade : 8 }} } )

Results:

{
    "_id": ObjectId("58f65e1198f3a12c7090e68c"),
    "id": "WakefieldFamily",
    "parents": [{
        "familyName": "Wakefield",
        "givenName": "Robin"
    }, {
        "familyName": "Miller",
        "givenName": "Ben"
    }],
    "children": [{
        "familyName": "Merriam",
        "givenName": "Jesse",
        "gender": "female",
        "grade": 1,
        "pets": [{
            "givenName": "Goofy"
        }, {
            "givenName": "Shadow"
        }]
    }, {
        "familyName": "Miller",
        "givenName": "Lisa",
        "gender": "female",
        "grade": 8
    }],
    "address": {
        "state": "NY",
        "county": "Manhattan",
        "city": "NY"
    },
    "creationDate": 1431620462,
    "isRegistered": false
}

Example query 7

The next query returns all the families where size of children array is 3.

Query:

db.Family.find( {children: { $size:3} } )

Results:

No results are returned because there are no families with more than two children. Only when parameter value is 2 does this query succeed and return the full document.

Next steps

In this tutorial, you've done the following tasks:

  • Learned how to query using Azure Cosmos DB for MongoDB

You can now proceed to the next tutorial to learn how to distribute your data multiple-regionally.

Distribute your data multiple-regionally