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MongoDB CRUD Operations

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Query Documents

Query an Array of Embedded Documents

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Query for a Document Nested in an Array

Specify a Query Condition on a Field in an Array of Documents
Specify Multiple Conditions for Array of Documents
Query an Array of Documents with MongoDB Atlas
Additional Query Tutorials

This version of the documentation is archived and no longer supported. View the current documentation to learn how to upgrade your version of MongoDB.

You can query documents in MongoDB by using the following methods:

Your programming language's driver.
The MongoDB Atlas UI. To learn more, see Query an Array of Documents with MongoDB Atlas.
MongoDB Compass.

➤ Use the Select your language drop-down menu in the upper-right to set the language of the following examples or select MongoDB Compass.

This page provides examples of query operations on an array of nested documents using the db.collection.find() method in mongo.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on an array of nested documents using MongoDB Compass.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on an array of nested documents using the MongoCollection.Find() method in the MongoDB C# Driver.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on an array of nested documents using the Collection.Find function in the MongoDB Go Driver.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on an array of nested documents using the com.mongodb.reactivestreams.client.MongoCollection.find method in the MongoDB Java Reactive Streams Driver.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on an array of nested documents using the com.mongodb.client.MongoCollection.find method in the MongoDB Java Synchronous Driver.

Tip

The driver provides com.mongodb.client.model.Filters helper methods to facilitate the creation of filter documents. The examples on this page use these methods to create the filter documents.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on an array of nested documents using the motor.motor_asyncio.AsyncIOMotorCollection.find method in the Motor driver.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on an array of nested documents using the Collection.find() method in the MongoDB Node.js Driver.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on an array of nested documents using the MongoDB::Collection::find() method in the MongoDB Perl Driver.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on an array of nested documents using the MongoDB\\Collection::find() method in the MongoDB PHP Library.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on an array of nested documents using the pymongo.collection.Collection.find method in the PyMongo Python driver.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on an array of nested documents using the Mongo::Collection#find() method in the MongoDB Ruby Driver.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on an array of nested documents using the collection.find() method in the MongoDB Scala Driver.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

db.inventory.insertMany( [
   { item: "journal", instock: [ { warehouse: "A", qty: 5 }, { warehouse: "C", qty: 15 } ] },
   { item: "notebook", instock: [ { warehouse: "C", qty: 5 } ] },
   { item: "paper", instock: [ { warehouse: "A", qty: 60 }, { warehouse: "B", qty: 15 } ] },
   { item: "planner", instock: [ { warehouse: "A", qty: 40 }, { warehouse: "B", qty: 5 } ] },
   { item: "postcard", instock: [ { warehouse: "B", qty: 15 }, { warehouse: "C", qty: 35 } ] }
]);

[
    { "item": "journal", "instock": [ { "warehouse": "A", "qty": 5 }, { "warehouse": "C", "qty": 15 } ] },
    { "item": "notebook", "instock": [ { "warehouse": "C", "qty": 5 } ] },
    { "item": "paper", "instock": [ { "warehouse": "A", "qty": 60 }, { "warehouse": "B", "qty": 15 } ] },
    { "item": "planner", "instock": [ { "warehouse": "A", "qty": 40 }, { "warehouse": "B", "qty": 5 } ] },
    { "item": "postcard", "instock": [ { "warehouse": "B","qty": 15 }, { "warehouse": "C", "qty": 35 } ] }
]

For instructions on inserting documents in MongoDB Compass, see Insert Documents.

var documents = new[]
{
    new BsonDocument
    {
        { "item", "journal" },
        { "instock", new BsonArray
            {
                new BsonDocument { { "warehouse", "A" }, { "qty", 5 } },
                new BsonDocument { { "warehouse", "C" }, { "qty", 15 } } }
            }
    },
    new BsonDocument
    {
        { "item", "notebook" },
        { "instock", new BsonArray
            {
                new BsonDocument { { "warehouse", "C" }, { "qty", 5 } } }
            }
    },
    new BsonDocument
    {
        { "item", "paper" },
        { "instock", new BsonArray
            {
                new BsonDocument { { "warehouse", "A" }, { "qty", 60 } },
                new BsonDocument { { "warehouse", "B" }, { "qty", 15 } } }
            }
    },
    new BsonDocument
    {
        { "item", "planner" },
        { "instock", new BsonArray
            {
                new BsonDocument { { "warehouse", "A" }, { "qty", 40 } },
                new BsonDocument { { "warehouse", "B" }, { "qty", 5 } } }
            }
    },
    new BsonDocument
    {
        { "item", "postcard" },
        { "instock", new BsonArray
            {
                new BsonDocument { { "warehouse", "B" }, { "qty", 15 } },
                new BsonDocument { { "warehouse", "C" }, { "qty", 35 } } }
            }
    }
};
collection.InsertMany(documents);

docs := []interface{}{
	bson.D{
		{"item", "journal"},
		{"instock", bson.A{
			bson.D{
				{"warehouse", "A"},
				{"qty", 5},
			},
			bson.D{
				{"warehouse", "C"},
				{"qty", 15},
			},
		}},
	},
	bson.D{
		{"item", "notebook"},
		{"instock", bson.A{
			bson.D{
				{"warehouse", "C"},
				{"qty", 5},
			},
		}},
	},
	bson.D{
		{"item", "paper"},
		{"instock", bson.A{
			bson.D{
				{"warehouse", "A"},
				{"qty", 60},
			},
			bson.D{
				{"warehouse", "B"},
				{"qty", 15},
			},
		}},
	},
	bson.D{
		{"item", "planner"},
		{"instock", bson.A{
			bson.D{
				{"warehouse", "A"},
				{"qty", 40},
			},
			bson.D{
				{"warehouse", "B"},
				{"qty", 5},
			},
		}},
	},
	bson.D{
		{"item", "postcard"},
		{"instock", bson.A{
			bson.D{
				{"warehouse", "B"},
				{"qty", 15},
			},
			bson.D{
				{"warehouse", "C"},
				{"qty", 35},
			},
		}},
	},
}
result, err := coll.InsertMany(context.TODO(), docs)

Publisher<Success> insertManyPublisher = collection.insertMany(asList(
        Document.parse("{ item: 'journal', instock: [ { warehouse: 'A', qty: 5 }, { warehouse: 'C', qty: 15 } ] }"),
        Document.parse("{ item: 'notebook', instock: [ { warehouse: 'C', qty: 5 } ] }"),
        Document.parse("{ item: 'paper', instock: [ { warehouse: 'A', qty: 60 }, { warehouse: 'B', qty: 15 } ] }"),
        Document.parse("{ item: 'planner', instock: [ { warehouse: 'A', qty: 40 }, { warehouse: 'B', qty: 5 } ] }"),
        Document.parse("{ item: 'postcard', instock: [ { warehouse: 'B', qty: 15 }, { warehouse: 'C', qty: 35 } ] }")
));

collection.insertMany(asList(
        Document.parse("{ item: 'journal', instock: [ { warehouse: 'A', qty: 5 }, { warehouse: 'C', qty: 15 } ] }"),
        Document.parse("{ item: 'notebook', instock: [ { warehouse: 'C', qty: 5 } ] }"),
        Document.parse("{ item: 'paper', instock: [ { warehouse: 'A', qty: 60 }, { warehouse: 'B', qty: 15 } ] }"),
        Document.parse("{ item: 'planner', instock: [ { warehouse: 'A', qty: 40 }, { warehouse: 'B', qty: 5 } ] }"),
        Document.parse("{ item: 'postcard', instock: [ { warehouse: 'B', qty: 15 }, { warehouse: 'C', qty: 35 } ] }")
));

# Subdocument key order matters in a few of these examples so we have
# to use bson.son.SON instead of a Python dict.
from bson.son import SON
await db.inventory.insert_many(
    [
        {
            "item": "journal",
            "instock": [
                SON([("warehouse", "A"), ("qty", 5)]),
                SON([("warehouse", "C"), ("qty", 15)]),
            ],
        },
        {"item": "notebook", "instock": [SON([("warehouse", "C"), ("qty", 5)])]},
        {
            "item": "paper",
            "instock": [
                SON([("warehouse", "A"), ("qty", 60)]),
                SON([("warehouse", "B"), ("qty", 15)]),
            ],
        },
        {
            "item": "planner",
            "instock": [
                SON([("warehouse", "A"), ("qty", 40)]),
                SON([("warehouse", "B"), ("qty", 5)]),
            ],
        },
        {
            "item": "postcard",
            "instock": [
                SON([("warehouse", "B"), ("qty", 15)]),
                SON([("warehouse", "C"), ("qty", 35)]),
            ],
        },
    ]
)

await db.collection('inventory').insertMany([
  {
    item: 'journal',
    instock: [
      { warehouse: 'A', qty: 5 },
      { warehouse: 'C', qty: 15 }
    ]
  },
  {
    item: 'notebook',
    instock: [{ warehouse: 'C', qty: 5 }]
  },
  {
    item: 'paper',
    instock: [
      { warehouse: 'A', qty: 60 },
      { warehouse: 'B', qty: 15 }
    ]
  },
  {
    item: 'planner',
    instock: [
      { warehouse: 'A', qty: 40 },
      { warehouse: 'B', qty: 5 }
    ]
  },
  {
    item: 'postcard',
    instock: [
      { warehouse: 'B', qty: 15 },
      { warehouse: 'C', qty: 35 }
    ]
  }
]);

# Subdocument key order matters in this example so we have
# to use Tie::IxHash instead of a regular, unordered Perl hash.
$db->coll("inventory")->insert_many(
    [
        {
            item    => "journal",
            instock => [
                Tie::IxHash->new( warehouse => "A", qty => 5 ),
                Tie::IxHash->new( warehouse => "C", qty => 15 )
            ]
        },
        {
            item    => "notebook",
            instock => [ Tie::IxHash->new( warehouse => "C", qty => 5 ) ]
        },
        {
            item    => "paper",
            instock => [
                Tie::IxHash->new( warehouse => "A", qty => 60 ),
                Tie::IxHash->new( warehouse => "B", qty => 15 )
            ]
        },
        {
            item    => "planner",
            instock => [
                Tie::IxHash->new( warehouse => "A", qty => 40 ),
                Tie::IxHash->new( warehouse => "B", qty => 5 )
            ]
        },
        {
            item    => "postcard",
            instock => [
                Tie::IxHash->new( warehouse => "B", qty => 15 ),
                Tie::IxHash->new( warehouse => "C", qty => 35 )
            ]
        }
    ]
);

$insertManyResult = $db->inventory->insertMany([
    [
        'item' => 'journal',
        'instock' => [
            ['warehouse' => 'A',  'qty' => 5],
            ['warehouse' => 'C',  'qty' => 15],
        ],
    ],
    [
        'item' => 'notebook',
        'instock' => [
            ['warehouse' => 'C',  'qty' => 5],
        ],
    ],
    [
        'item' => 'paper',
        'instock' => [
            ['warehouse' => 'A',  'qty' => 60],
            ['warehouse' => 'B',  'qty' => 15],
        ],
    ],
    [
        'item' => 'planner',
        'instock' => [
            ['warehouse' => 'A',  'qty' => 40],
            ['warehouse' => 'B',  'qty' => 5],
        ],
    ],
    [
        'item' => 'postcard',
        'instock' => [
            ['warehouse' => 'B',  'qty' => 15],
            ['warehouse' => 'C',  'qty' => 35],
        ],
    ],
]);

# Subdocument key order matters in a few of these examples so we have
# to use bson.son.SON instead of a Python dict.
from bson.son import SON
db.inventory.insert_many(
    [
        {
            "item": "journal",
            "instock": [
                SON([("warehouse", "A"), ("qty", 5)]),
                SON([("warehouse", "C"), ("qty", 15)]),
            ],
        },
        {"item": "notebook", "instock": [SON([("warehouse", "C"), ("qty", 5)])]},
        {
            "item": "paper",
            "instock": [
                SON([("warehouse", "A"), ("qty", 60)]),
                SON([("warehouse", "B"), ("qty", 15)]),
            ],
        },
        {
            "item": "planner",
            "instock": [
                SON([("warehouse", "A"), ("qty", 40)]),
                SON([("warehouse", "B"), ("qty", 5)]),
            ],
        },
        {
            "item": "postcard",
            "instock": [
                SON([("warehouse", "B"), ("qty", 15)]),
                SON([("warehouse", "C"), ("qty", 35)]),
            ],
        },
    ]
)

client[:inventory].insert_many([{ item: 'journal',
                                  instock: [ { warehouse: 'A', qty: 5 },
                                             { warehouse: 'C', qty: 15 }] },
                                { item: 'notebook',
                                  instock: [ { warehouse: 'C', qty: 5 }] },
                                { item: 'paper',
                                  instock: [ { warehouse: 'A', qty: 60 },
                                             { warehouse: 'B', qty: 15 }] },
                                { item: 'planner',
                                  instock: [ { warehouse: 'A', qty: 40 },
                                             { warehouse: 'B', qty: 5 }] },
                                { item: 'postcard',
                                  instock: [ { warehouse: 'B', qty: 15 },
                                             { warehouse: 'C', qty: 35 }] }
                               ])

collection.insertMany(Seq(
  Document("""{ item: "journal", instock: [ { warehouse: "A", qty: 5 }, { warehouse: "C", qty: 15 } ] }"""),
  Document("""{ item: "notebook", instock: [ { warehouse: "C", qty: 5 } ] }"""),
  Document("""{ item: "paper", instock: [ { warehouse: "A", qty: 60 }, { warehouse: "B", qty: 15 } ] }"""),
  Document("""{ item: "planner", instock: [ { warehouse: "A", qty: 40 }, { warehouse: "B", qty: 5 } ] }"""),
  Document("""{ item: "postcard", instock: [ { warehouse: "B", qty: 15 }, { warehouse: "C", qty: 35 } ] }""")
)).execute()

Query for a Document Nested in an Array

The following example selects all documents where an element in the instock array matches the specified document:

db.inventory.find( { "instock": { warehouse: "A", qty: 5 } } )

Copy the following filter into the Compass query bar and click Find:

{ "instock": { warehouse: "A", qty: 5 } }

Query for nested array element

var filter = Builders<BsonDocument>.Filter.AnyEq("instock", new BsonDocument { { "warehouse", "A" }, { "qty", 5 } });
var result = collection.Find(filter).ToList();

cursor, err := coll.Find(
	context.TODO(),
	bson.D{
		{"instock", bson.D{
			{"warehouse", "A"},
			{"qty", 5},
		}},
	})

FindPublisher<Document> findPublisher = collection.find(eq("instock", Document.parse("{ warehouse: 'A', qty: 5 }")));

FindIterable<Document> findIterable = collection.find(eq("instock", Document.parse("{ warehouse: 'A', qty: 5 }")));

cursor = db.inventory.find({"instock": SON([("warehouse", "A"), ("qty", 5)])})

const cursor = db.collection('inventory').find({
  instock: { warehouse: 'A', qty: 5 }
});

# Subdocument key order matters in this example so we have
# to use Tie::IxHash instead of a regular, unordered Perl hash.
$cursor = $db->coll("inventory")->find(
    { instock => Tie::IxHash->new( warehouse => "A", qty => 5 ) }
);

$cursor = $db->inventory->find(['instock' => ['warehouse' => 'A', 'qty' => 5]]);

cursor = db.inventory.find({"instock": SON([("warehouse", "A"), ("qty", 5)])})

client[:inventory].find(instock: { warehouse: 'A', qty: 5 })

var findObservable = collection.find(equal("instock", Document("warehouse" -> "A", "qty" -> 5)))

Equality matches on the whole embedded/nested document require an exact match of the specified document, including the field order. For example, the following query does not match any documents in the inventory collection:

db.inventory.find( { "instock": { qty: 5, warehouse: "A" } } )

Query for nested array element

var filter = Builders<BsonDocument>.Filter.AnyEq("instock", new BsonDocument { { "qty", 5 }, { "warehouse", "A" } });
var result = collection.Find(filter).ToList();

cursor, err := coll.Find(
	context.TODO(),
	bson.D{
		{"instock", bson.D{
			{"qty", 5},
			{"warehouse", "A"},
		}},
	})

findPublisher = collection.find(eq("instock", Document.parse("{ qty: 5, warehouse: 'A' }")));

findIterable = collection.find(eq("instock", Document.parse("{ qty: 5, warehouse: 'A' }")));

cursor = db.inventory.find({"instock": SON([("qty", 5), ("warehouse", "A")])})

const cursor = db.collection('inventory').find({
  instock: { qty: 5, warehouse: 'A' }
});

# Subdocument key order matters in this example so we have
# to use Tie::IxHash instead of a regular, unordered Perl hash.
$cursor = $db->coll("inventory")->find(
    { instock => Tie::IxHash->new( qty => 5, warehouse => "A" ) }
);

$cursor = $db->inventory->find(['instock' => ['qty' => 5, 'warehouse' => 'A']]);

cursor = db.inventory.find({"instock": SON([("qty", 5), ("warehouse", "A")])})

client[:inventory].find(instock: { qty: 5, warehouse: 'A' } )

findObservable = collection.find(equal("instock", Document("qty" -> 5, "warehouse" -> "A")))

Specify a Query Condition on a Field in an Array of Documents

Specify a Query Condition on a Field Embedded in an Array of Documents

If you do not know the index position of the document nested in the array, concatenate the name of the array field, with a dot (.) and the name of the field in the nested document.

The following example selects all documents where the instock array has at least one embedded document that contains the field qty whose value is less than or equal to 20:

db.inventory.find( { 'instock.qty': { $lte: 20 } } )

Copy the following filter into the Compass query bar and click Find:

{ 'instock.qty': { $lte: 20 } }

Query for embedded field matching single condition

var filter = Builders<BsonDocument>.Filter.Lte("instock.qty", 20);
var result = collection.Find(filter).ToList();

cursor, err := coll.Find(
	context.TODO(),
	bson.D{
		{"instock.qty", bson.D{
			{"$lte", 20},
		}},
	})

findPublisher = collection.find(lte("instock.qty", 20));

findIterable = collection.find(lte("instock.qty", 20));

cursor = db.inventory.find({"instock.qty": {"$lte": 20}})

const cursor = db.collection('inventory').find({
  'instock.qty': { $lte: 20 }
});

$cursor = $db->coll("inventory")->find( { 'instock.qty' => { '$lte' => 20 } } );

$cursor = $db->inventory->find(['instock.qty' => ['$lte' => 20]]);

cursor = db.inventory.find({"instock.qty": {"$lte": 20}})

client[:inventory].find('instock.qty' => { '$lte' => 20 })

findObservable = collection.find(lte("instock.qty", 20))

Use the Array Index to Query for a Field in the Embedded Document

Using dot notation, you can specify query conditions for field in a document at a particular index or position of the array. The array uses zero-based indexing.

Note

When querying using dot notation, the field and index must be inside quotation marks.

The following example selects all documents where the instock array has as its first element a document that contains the field qty whose value is less than or equal to 20:

db.inventory.find( { 'instock.0.qty': { $lte: 20 } } )

Copy the following filter into the Compass query bar and click Find:

{ 'instock.0.qty': { $lte: 20 } }

Query for array element matching single condition

var filter = Builders<BsonDocument>.Filter.Lte("instock.0.qty", 20);
var result = collection.Find(filter).ToList();

cursor, err := coll.Find(
	context.TODO(),
	bson.D{
		{"instock.0.qty", bson.D{
			{"$lte", 20},
		}},
	})

findPublisher = collection.find(lte("instock.0.qty", 20));

findIterable = collection.find(lte("instock.0.qty", 20));

cursor = db.inventory.find({"instock.0.qty": {"$lte": 20}})

const cursor = db.collection('inventory').find({
  'instock.0.qty': { $lte: 20 }
});

$cursor = $db->coll("inventory")->find( { 'instock.0.qty' => { '$lte' => 20 } } );

$cursor = $db->inventory->find(['instock.0.qty' => ['$lte' => 20]]);

cursor = db.inventory.find({"instock.0.qty": {"$lte": 20}})

client[:inventory].find('instock.0.qty' => { '$lte' => 20 })

findObservable = collection.find(lte("instock.0.qty", 20))

Specify Multiple Conditions for Array of Documents

When specifying conditions on more than one field nested in an array of documents, you can specify the query such that either a single document meets these condition or any combination of documents (including a single document) in the array meets the conditions.

A Single Nested Document Meets Multiple Query Conditions on Nested Fields

Use $elemMatch operator to specify multiple criteria on an array of embedded documents such that at least one embedded document satisfies all the specified criteria.

The following example queries for documents where the instock array has at least one embedded document that contains both the field qty equal to 5 and the field warehouse equal to A:

db.inventory.find( { "instock": { $elemMatch: { qty: 5, warehouse: "A" } } } )

Copy the following filter into the Compass query bar and click Find:

{ "instock": { $elemMatch: { qty: 5, warehouse: "A" } } }

Query for single document matching multiple conditions

var filter = Builders<BsonDocument>.Filter.ElemMatch<BsonValue>("instock", new BsonDocument { { "qty", 5 }, { "warehouse", "A" } });
var result = collection.Find(filter).ToList();

cursor, err := coll.Find(
	context.TODO(),
	bson.D{
		{"instock", bson.D{
			{"$elemMatch", bson.D{
				{"qty", 5},
				{"warehouse", "A"},
			}},
		}},
	})

findPublisher = collection.find(elemMatch("instock", Document.parse("{ qty: 5, warehouse: 'A' }")));

findIterable = collection.find(elemMatch("instock", Document.parse("{ qty: 5, warehouse: 'A' }")));

cursor = db.inventory.find({"instock": {"$elemMatch": {"qty": 5, "warehouse": "A"}}})

const cursor = db.collection('inventory').find({
  instock: { $elemMatch: { qty: 5, warehouse: 'A' } }
});

$cursor = $db->coll("inventory")->find(
    { instock => { '$elemMatch' => { qty => 5, warehouse => "A" } } }
);

$cursor = $db->inventory->find(['instock' => ['$elemMatch' => ['qty' => 5, 'warehouse' => 'A']]]);

cursor = db.inventory.find({"instock": {"$elemMatch": {"qty": 5, "warehouse": "A"}}})

client[:inventory].find(instock: { '$elemMatch' => { qty: 5,
                                                     warehouse: 'A' } })

findObservable = collection.find(elemMatch("instock", Document("qty" -> 5, "warehouse" -> "A")))

The following example queries for documents where the instock array has at least one embedded document that contains the field qty that is greater than 10 and less than or equal to 20:

db.inventory.find( { "instock": { $elemMatch: { qty: { $gt: 10, $lte: 20 } } } } )

Copy the following filter into the Compass query bar and click Find:

{ "instock": { $elemMatch: { qty: { $gt: 10, $lte: 20 } } } }

Query for single document matching multiple conditions

var filter = Builders<BsonDocument>.Filter.ElemMatch<BsonValue>("instock", new BsonDocument { { "qty", new BsonDocument { { "$gt", 10 }, { "$lte", 20 } } } });
var result = collection.Find(filter).ToList();

cursor, err := coll.Find(
	context.TODO(),
	bson.D{
		{"instock", bson.D{
			{"$elemMatch", bson.D{
				{"qty", bson.D{
					{"$gt", 10},
					{"$lte", 20},
				}},
			}},
		}},
	})

findPublisher = collection.find(elemMatch("instock", Document.parse("{ qty: { $gt: 10, $lte: 20 } }")));

findIterable = collection.find(elemMatch("instock", Document.parse("{ qty: { $gt: 10, $lte: 20 } }")));

cursor = db.inventory.find({"instock": {"$elemMatch": {"qty": {"$gt": 10, "$lte": 20}}}})

const cursor = db.collection('inventory').find({
  instock: { $elemMatch: { qty: { $gt: 10, $lte: 20 } } }
});

$cursor = $db->coll("inventory") ->find(
    { instock => { '$elemMatch' => { qty => { '$gt' => 10, '$lte' => 20 } } } }
);

$cursor = $db->inventory->find(['instock' => ['$elemMatch' => ['qty' => ['$gt' => 10, '$lte' => 20]]]]);

cursor = db.inventory.find({"instock": {"$elemMatch": {"qty": {"$gt": 10, "$lte": 20}}}})

client[:inventory].find(instock: { '$elemMatch' => { qty: { '$gt'  => 10,
                                                            '$lte' => 20 } } })

findObservable = collection.find(elemMatch("instock", Document("""{ qty: { $gt: 10, $lte: 20 } }""")))

Combination of Elements Satisfies the Criteria

If the compound query conditions on an array field do not use the $elemMatch operator, the query selects those documents whose array contains any combination of elements that satisfies the conditions.

For example, the following query matches documents where any document nested in the instock array has the qty field greater than 10 and any document (but not necessarily the same embedded document) in the array has the qty field less than or equal to 20:

db.inventory.find( { "instock.qty": { $gt: 10,  $lte: 20 } } )

Copy the following filter into the Compass query bar and click Find:

{ "instock.qty": { $gt: 10,  $lte: 20 } }

Query quantity value within range

var builder = Builders<BsonDocument>.Filter;
var filter = builder.And(builder.Gt("instock.qty", 10), builder.Lte("instock.qty", 20));
var result = collection.Find(filter).ToList();

cursor, err := coll.Find(
	context.TODO(),
	bson.D{
		{"instock.qty", bson.D{
			{"$gt", 10},
			{"$lte", 20},
		}},
	})

findPublisher = collection.find(and(gt("instock.qty", 10), lte("instock.qty", 20)));

findIterable = collection.find(and(gt("instock.qty", 10), lte("instock.qty", 20)));

cursor = db.inventory.find({"instock.qty": {"$gt": 10, "$lte": 20}})

const cursor = db.collection('inventory').find({
  'instock.qty': { $gt: 10, $lte: 20 }
});

$cursor = $db->coll("inventory")->find(
    { "instock.qty" => { '$gt' => 10, '$lte' => 20 } }
);

$cursor = $db->inventory->find(['instock.qty' => ['$gt' => 10, '$lte' => 20]]);

cursor = db.inventory.find({"instock.qty": {"$gt": 10, "$lte": 20}})

client[:inventory].find('instock.qty' => { '$gt' => 10, '$lte' => 20 })

findObservable = collection.find(and(gt("instock.qty", 10), lte("instock.qty", 20)))

The following example queries for documents where the instock array has at least one embedded document that contains the field qty equal to 5 and at least one embedded document (but not necessarily the same embedded document) that contains the field warehouse equal to A:

db.inventory.find( { "instock.qty": 5, "instock.warehouse": "A" } )

Copy the following filter into the Compass query bar and click Find:

{ "instock.qty": 5, "instock.warehouse": "A" }

Query matching quantity and warehouse location

var builder = Builders<BsonDocument>.Filter;
var filter = builder.And(builder.Eq("instock.qty", 5), builder.Eq("instock.warehouse", "A"));
var result = collection.Find(filter).ToList();

cursor, err := coll.Find(
	context.TODO(),
	bson.D{
		{"instock.qty", 5},
		{"instock.warehouse", "A"},
	})

findPublisher = collection.find(and(eq("instock.qty", 5), eq("instock.warehouse", "A")));

findIterable = collection.find(and(eq("instock.qty", 5), eq("instock.warehouse", "A")));

cursor = db.inventory.find({"instock.qty": 5, "instock.warehouse": "A"})

const cursor = db.collection('inventory').find({
  'instock.qty': 5,
  'instock.warehouse': 'A'
});

$cursor = $db->coll("inventory")->find(
    { "instock.qty" => 5, "instock.warehouse" => "A" }
);

$cursor = $db->inventory->find(['instock.qty' => 5, 'instock.warehouse' => 'A']);

cursor = db.inventory.find({"instock.qty": 5, "instock.warehouse": "A"})

client[:inventory].find('instock.qty' => 5,
                        'instock.warehouse' => 'A')

findObservable = collection.find(and(equal("instock.qty", 5), equal("instock.warehouse", "A")))

Query an Array of Documents with MongoDB Atlas

The example in this section uses the sample training dataset. To learn how to load the sample dataset into your MongoDB Atlas deployment, see Load Sample Data.

To query an array of documents in MongoDB Atlas, follow these steps:

1

Navigate to the collection

In the MongoDB Atlas UI, click Database in the sidebar.
For the database deployment that contains the sample data, click Browse Collections.
In the left navigation pane, select the sample_training database.
Select the grades collection.

2

Specify the Filter field

Specify the query filter document in the Filter field. A query filter document uses query operators to specify search conditions.

Copy the following query filter document into the Filter search bar:

{ scores: { type: "exam" } }

3

Click Apply

This query filter returns all documents in the sample_training.grades collection where the scores field contains an exam score type.

Additional Query Tutorials

For additional query examples, see:

Back

Query an Array

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Project Fields to Return from Query

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On this page

Query for a Document Nested in an Array
Specify a Query Condition on a Field in an Array of Documents
Specify Multiple Conditions for Array of Documents
Query an Array of Documents with MongoDB Atlas
Additional Query Tutorials