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CRUD Operations

Query Documents

On this page

Select All Documents in a Collection

Specify Equality Condition
Specify Conditions Using Query Operators
Specify AND Conditions
Specify OR Conditions
Specify AND as well as OR Conditions
Query Documents with MongoDB Atlas
Additional Query Tutorials
Behavior
Additional Methods and Options

To query documents, specify a query predicate indicating the documents you want to return. If you specify an empty query predicate ({ }), the query returns all documents in the collection.

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 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 using the db.collection.find() method in mongosh.

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 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 using mongoc_collection_find_with_opts.

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 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 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 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 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 by using the MongoCollection.find() method in the MongoDB Kotlin Coroutine 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 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 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 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 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 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 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", qty: 25, size: { h: 14, w: 21, uom: "cm" }, status: "A" },
   { item: "notebook", qty: 50, size: { h: 8.5, w: 11, uom: "in" }, status: "A" },
   { item: "paper", qty: 100, size: { h: 8.5, w: 11, uom: "in" }, status: "D" },
   { item: "planner", qty: 75, size: { h: 22.85, w: 30, uom: "cm" }, status: "D" },
   { item: "postcard", qty: 45, size: { h: 10, w: 15.25, uom: "cm" }, status: "A" }
]);

[
    { "item": "journal", "qty": 25, "size": { "h": 14, "w": 21, "uom": "cm" }, "status": "A" },
    { "item": "notebook", "qty": 50, "size": { "h": 8.5, "w": 11, "uom": "in" }, "status": "A" },
    { "item": "paper", "qty": 100, "size": { "h": 8.5, "w": 11, "uom": "in" }, "status": "D" },
    { "item": "planner", "qty": 75, "size": { "h": 22.85, "w": 30, "uom": "cm" }, "status": "D" },
    { "item": "postcard", "qty": 45, "size": { "h": 10, "w": 15.25, "uom": "cm" }, "status": "A" }
]

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

mongoc_collection_t *collection;
mongoc_bulk_operation_t *bulk;
bson_t *doc;
bool r;
bson_error_t error;
bson_t reply;
collection = mongoc_database_get_collection (db, "inventory");
bulk = mongoc_collection_create_bulk_operation_with_opts (collection, NULL);
doc = BCON_NEW (
   "item", BCON_UTF8 ("journal"),
   "qty", BCON_INT64 (25),
   "size", "{",
   "h", BCON_DOUBLE (14),
   "w", BCON_DOUBLE (21),
   "uom", BCON_UTF8 ("cm"),
   "}",
   "status", BCON_UTF8 ("A"));
r = mongoc_bulk_operation_insert_with_opts (bulk, doc, NULL, &error);
bson_destroy (doc);
if (!r) {
   MONGOC_ERROR ("%s\n", error.message);
   goto done;
}
doc = BCON_NEW (
   "item", BCON_UTF8 ("notebook"),
   "qty", BCON_INT64 (50),
   "size", "{",
   "h", BCON_DOUBLE (8.5),
   "w", BCON_DOUBLE (11),
   "uom", BCON_UTF8 ("in"),
   "}",
   "status", BCON_UTF8 ("A"));
r = mongoc_bulk_operation_insert_with_opts (bulk, doc, NULL, &error);
bson_destroy (doc);
if (!r) {
   MONGOC_ERROR ("%s\n", error.message);
   goto done;
}
doc = BCON_NEW (
   "item", BCON_UTF8 ("paper"),
   "qty", BCON_INT64 (100),
   "size", "{",
   "h", BCON_DOUBLE (8.5),
   "w", BCON_DOUBLE (11),
   "uom", BCON_UTF8 ("in"),
   "}",
   "status", BCON_UTF8 ("D"));
r = mongoc_bulk_operation_insert_with_opts (bulk, doc, NULL, &error);
bson_destroy (doc);
if (!r) {
   MONGOC_ERROR ("%s\n", error.message);
   goto done;
}
doc = BCON_NEW (
   "item", BCON_UTF8 ("planner"),
   "qty", BCON_INT64 (75),
   "size", "{",
   "h", BCON_DOUBLE (22.85),
   "w", BCON_DOUBLE (30),
   "uom", BCON_UTF8 ("cm"),
   "}",
   "status", BCON_UTF8 ("D"));
r = mongoc_bulk_operation_insert_with_opts (bulk, doc, NULL, &error);
bson_destroy (doc);
if (!r) {
   MONGOC_ERROR ("%s\n", error.message);
   goto done;
}
doc = BCON_NEW (
   "item", BCON_UTF8 ("postcard"),
   "qty", BCON_INT64 (45),
   "size", "{",
   "h", BCON_DOUBLE (10),
   "w", BCON_DOUBLE (15.25),
   "uom", BCON_UTF8 ("cm"),
   "}",
   "status", BCON_UTF8 ("A"));
r = mongoc_bulk_operation_insert_with_opts (bulk, doc, NULL, &error);
bson_destroy (doc);
if (!r) {
   MONGOC_ERROR ("%s\n", error.message);
   goto done;
}
/* "reply" is initialized on success or error */
r = (bool) mongoc_bulk_operation_execute (bulk, &reply, &error);
if (!r) {
   MONGOC_ERROR ("%s\n", error.message);
}

var documents = new BsonDocument[]
{
    new BsonDocument
    {
        { "item", "journal" },
        { "qty", 25 },
        { "size", new BsonDocument { { "h", 14 }, { "w", 21 }, {  "uom", "cm"} } },
        { "status", "A" }
    },
    new BsonDocument
    {
        { "item", "notebook" },
        { "qty", 50 },
        { "size", new BsonDocument { { "h",  8.5 }, { "w", 11 }, {  "uom", "in"} } },
        { "status", "A" }
    },
    new BsonDocument
    {
        { "item", "paper" },
        { "qty", 100 },
        { "size", new BsonDocument { { "h",  8.5 }, { "w", 11 }, {  "uom", "in"} } },
        { "status", "D" }
    },
    new BsonDocument
    {
        { "item", "planner" },
        { "qty", 75 },
        { "size", new BsonDocument { { "h", 22.85 }, { "w", 30  }, {  "uom", "cm"} } },
        { "status", "D" }
    },
    new BsonDocument
    {
        { "item", "postcard" },
        { "qty", 45 },
        { "size", new BsonDocument { { "h", 10 }, { "w", 15.25 }, {  "uom", "cm"} } },
        { "status", "A" }
    },
};
collection.InsertMany(documents);

docs := []interface{}{
	bson.D{
		{"item", "journal"},
		{"qty", 25},
		{"size", bson.D{
			{"h", 14},
			{"w", 21},
			{"uom", "cm"},
		}},
		{"status", "A"},
	},
	bson.D{
		{"item", "notebook"},
		{"qty", 50},
		{"size", bson.D{
			{"h", 8.5},
			{"w", 11},
			{"uom", "in"},
		}},
		{"status", "A"},
	},
	bson.D{
		{"item", "paper"},
		{"qty", 100},
		{"size", bson.D{
			{"h", 8.5},
			{"w", 11},
			{"uom", "in"},
		}},
		{"status", "D"},
	},
	bson.D{
		{"item", "planner"},
		{"qty", 75},
		{"size", bson.D{
			{"h", 22.85},
			{"w", 30},
			{"uom", "cm"},
		}},
		{"status", "D"},
	},
	bson.D{
		{"item", "postcard"},
		{"qty", 45},
		{"size", bson.D{
			{"h", 10},
			{"w", 15.25},
			{"uom", "cm"},
		}},
		{"status", "A"},
	},
}
result, err := coll.InsertMany(context.TODO(), docs)

Publisher<Success> insertManyPublisher = collection.insertMany(asList(
        Document.parse("{ item: 'journal', qty: 25, size: { h: 14, w: 21, uom: 'cm' }, status: 'A' }"),
        Document.parse("{ item: 'notebook', qty: 50, size: { h: 8.5, w: 11, uom: 'in' }, status: 'A' }"),
        Document.parse("{ item: 'paper', qty: 100, size: { h: 8.5, w: 11, uom: 'in' }, status: 'D' }"),
        Document.parse("{ item: 'planner', qty: 75, size: { h: 22.85, w: 30, uom: 'cm' }, status: 'D' }"),
        Document.parse("{ item: 'postcard', qty: 45, size: { h: 10, w: 15.25, uom: 'cm' }, status: 'A' }")
));

collection.insertMany(asList(
        Document.parse("{ item: 'journal', qty: 25, size: { h: 14, w: 21, uom: 'cm' }, status: 'A' }"),
        Document.parse("{ item: 'notebook', qty: 50, size: { h: 8.5, w: 11, uom: 'in' }, status: 'A' }"),
        Document.parse("{ item: 'paper', qty: 100, size: { h: 8.5, w: 11, uom: 'in' }, status: 'D' }"),
        Document.parse("{ item: 'planner', qty: 75, size: { h: 22.85, w: 30, uom: 'cm' }, status: 'D' }"),
        Document.parse("{ item: 'postcard', qty: 45, size: { h: 10, w: 15.25, uom: 'cm' }, status: 'A' }")
));

collection.insertMany(
    listOf(
        Document("item", "journal")
            .append("qty", 25)
            .append("size", Document("h", 14)
                .append("w", 21)
                .append("uom", "cm")
            )
            .append("status", "A"),
        Document("item", "notebook")
            .append("qty", 50)
            .append("size", Document("h", 8.5)
                .append("w", 11)
                .append("uom", "in")
            )
            .append("status", "A"),
        Document("item", "paper")
            .append("qty", 100)
            .append("size", Document("h", 8.5)
                .append("w", 11)
                .append("uom", "in")
            )
            .append("status", "D"),
        Document("item", "planner")
            .append("qty", 75)
            .append("size", Document("h", 22.85)
                .append("w", 30)
                .append("uom", "cm")
            )
            .append("status", "D"),
        Document("item", "postcard")
            .append("qty", 45)
            .append("size", Document("h", 10)
                .append("w", 15.25)
                .append("uom", "cm")
            )
            .append("status", "A"),
    )
)

await db.inventory.insert_many(
    [
        {
            "item": "journal",
            "qty": 25,
            "size": {"h": 14, "w": 21, "uom": "cm"},
            "status": "A",
        },
        {
            "item": "notebook",
            "qty": 50,
            "size": {"h": 8.5, "w": 11, "uom": "in"},
            "status": "A",
        },
        {
            "item": "paper",
            "qty": 100,
            "size": {"h": 8.5, "w": 11, "uom": "in"},
            "status": "D",
        },
        {
            "item": "planner",
            "qty": 75,
            "size": {"h": 22.85, "w": 30, "uom": "cm"},
            "status": "D",
        },
        {
            "item": "postcard",
            "qty": 45,
            "size": {"h": 10, "w": 15.25, "uom": "cm"},
            "status": "A",
        },
    ]
)

await db.collection('inventory').insertMany([
  {
    item: 'journal',
    qty: 25,
    size: { h: 14, w: 21, uom: 'cm' },
    status: 'A'
  },
  {
    item: 'notebook',
    qty: 50,
    size: { h: 8.5, w: 11, uom: 'in' },
    status: 'A'
  },
  {
    item: 'paper',
    qty: 100,
    size: { h: 8.5, w: 11, uom: 'in' },
    status: 'D'
  },
  {
    item: 'planner',
    qty: 75,
    size: { h: 22.85, w: 30, uom: 'cm' },
    status: 'D'
  },
  {
    item: 'postcard',
    qty: 45,
    size: { h: 10, w: 15.25, uom: 'cm' },
    status: 'A'
  }
]);

$db->coll("inventory")->insert_many(
    [
        {
            item   => "journal",
            qty    => 25,
            size   => { h => 14, w => 21, uom => "cm" },
            status => "A"
        },
        {
            item   => "notebook",
            qty    => 50,
            size   => { h => 8.5, w => 11, uom => "in" },
            status => "A"
        },
        {
            item   => "paper",
            qty    => 100,
            size   => { h => 8.5, w => 11, uom => "in" },
            status => "D"
        },
        {
            item   => "planner",
            qty    => 75,
            size   => { h => 22.85, w => 30, uom => "cm" },
            status => "D"
        },
        {
            item   => "postcard",
            qty    => 45,
            size   => { h => 10, w => 15.25, uom => "cm" },
            status => "A"
        }
    ]
);

$insertManyResult = $db->inventory->insertMany([
    [
        'item' => 'journal',
        'qty' => 25,
        'size' => ['h' => 14, 'w' => 21, 'uom' => 'cm'],
        'status' => 'A',
    ],
    [
        'item' => 'notebook',
        'qty' => 50,
        'size' => ['h' => 8.5, 'w' => 11, 'uom' => 'in'],
        'status' => 'A',
    ],
    [
        'item' => 'paper',
        'qty' => 100,
        'size' => ['h' => 8.5, 'w' => 11, 'uom' => 'in'],
        'status' => 'D',
    ],
    [
        'item' => 'planner',
        'qty' => 75,
        'size' => ['h' => 22.85, 'w' => 30, 'uom' => 'cm'],
        'status' => 'D',
    ],
    [
        'item' => 'postcard',
        'qty' => 45,
        'size' => ['h' => 10, 'w' => 15.25, 'uom' => 'cm'],
        'status' => 'A',
    ],
]);

db.inventory.insert_many(
    [
        {
            "item": "journal",
            "qty": 25,
            "size": {"h": 14, "w": 21, "uom": "cm"},
            "status": "A",
        },
        {
            "item": "notebook",
            "qty": 50,
            "size": {"h": 8.5, "w": 11, "uom": "in"},
            "status": "A",
        },
        {
            "item": "paper",
            "qty": 100,
            "size": {"h": 8.5, "w": 11, "uom": "in"},
            "status": "D",
        },
        {
            "item": "planner",
            "qty": 75,
            "size": {"h": 22.85, "w": 30, "uom": "cm"},
            "status": "D",
        },
        {
            "item": "postcard",
            "qty": 45,
            "size": {"h": 10, "w": 15.25, "uom": "cm"},
            "status": "A",
        },
    ]
)

client[:inventory].insert_many([{ item: 'journal',
                                  qty: 25,
                                  size: { h: 14, w: 21, uom: 'cm' },
                                  status: 'A' },
                                { item: 'notebook',
                                  qty: 50,
                                  size: { h: 8.5, w: 11, uom: 'in' },
                                  status: 'A' },
                                { item: 'paper',
                                  qty: 100,
                                  size: { h: 8.5, w: 11, uom: 'in' },
                                  status: 'D' },
                                { item: 'planner',
                                  qty: 75,
                                  size: { h: 22.85, w: 30, uom: 'cm' },
                                  status: 'D' },
                                { item: 'postcard',
                                  qty: 45,
                                  size: { h: 10, w: 15.25, uom: 'cm' },
                                  status: 'A' }
                               ])

collection.insertMany(Seq(
  Document("""{ item: "journal", qty: 25, size: { h: 14, w: 21, uom: "cm" }, status: "A" }"""),
  Document("""{ item: "notebook", qty: 50, size: { h: 8.5, w: 11, uom: "in" }, status: "A" }"""),
  Document("""{ item: "paper", qty: 100, size: { h: 8.5, w: 11, uom: "in" }, status: "D" }"""),
  Document("""{ item: "planner", qty: 75, size: { h: 22.85, w: 30, uom: "cm" }, status: "D" }"""),
  Document("""{ item: "postcard", qty: 45, size: { h: 10, w: 15.25, uom: "cm" }, status: "A" }""")
)).execute()

Select All Documents in a Collection

To select all documents in the collection, pass an empty document as the query filter parameter to the find method. The query filter parameter determines the select criteria:

To select all documents in the collection, pass an empty document as the query filter parameter to the query bar. The query filter parameter determines the select criteria:

To select all documents in the collection, pass an empty document as the query filter parameter to the find method. The query filter parameter determines the select criteria:

To select all documents in the collection, pass an empty document as the query filter parameter to the find method. The query filter parameter determines the select criteria:

To select all documents in the collection, pass an empty document as the query filter parameter to the find method. The query filter parameter determines the select criteria:

To select all documents in the collection, pass an empty document as the query filter parameter to the find method. The query filter parameter determines the select criteria:

To select all documents in the collection, pass an empty document as the query filter parameter to the find method. The query filter parameter determines the select criteria:

To select all documents in the collection, pass an empty document as the query filter parameter to the find method. The query filter parameter determines the select criteria:

To select all documents in the collection, pass an empty document as the query filter parameter to the find method. The query filter parameter determines the select criteria:

To select all documents in the collection, pass an empty document as the query filter parameter to the find method. The query filter parameter determines the select criteria:

To select all documents in the collection, pass an empty document as the query filter parameter to the find method. The query filter parameter determines the select criteria:

To select all documents in the collection, pass an empty document as the query filter parameter to the find method. The query filter parameter determines the select criteria:

To select all documents in the collection, pass an empty document as the query filter parameter to the find method. The query filter parameter determines the select criteria:

To select all documents in the collection, pass an empty document as the query filter parameter to the find method. The query filter parameter determines the select criteria:

To select all documents in the collection, pass an empty document as the query filter parameter to the find method. The query filter parameter determines the select criteria:

db.inventory.find( {} )

Compass select all documents in collection

mongoc_collection_t *collection;
bson_t *filter;
mongoc_cursor_t *cursor;
collection = mongoc_database_get_collection (db, "inventory");
filter = BCON_NEW (NULL);
cursor = mongoc_collection_find_with_opts (collection, filter, NULL, NULL);

Be sure to also clean up any open resources by calling the following methods, as appropriate:

var filter = Builders<BsonDocument>.Filter.Empty;
var result = collection.Find(filter).ToList();

cursor, err := coll.Find(
	context.TODO(),
	bson.D{},
)

FindPublisher<Document> findPublisher = collection.find(new Document());

FindIterable<Document> findIterable = collection.find(new Document());

val flowInsertMany = collection
    .find(empty())

cursor = db.inventory.find({})

const cursor = db.collection('inventory').find({});

$cursor = $db->coll("inventory")->find( {} );

$cursor = $db->inventory->find([]);

cursor = db.inventory.find({})

client[:inventory].find({})

var findObservable = collection.find(Document())

This operation uses a query predicate of {}, which corresponds to the following SQL statement:

SELECT * FROM inventory

For more information on the syntax of the method, see find().

For more information on the MongoDB Compass query bar, see Query Bar.

For more information on the syntax of the method, see mongoc_collection_find_with_opts.

For more information on the syntax of the method, see Find().

For more information on the syntax of the method, see com.mongodb.reactivestreams.client.MongoCollection.find.

For more information on the syntax of the method, see com.mongodb.client.MongoCollection.find.

For more information on the syntax of the method, see MongoCollection.find().

To see supported options for the find() method, see find().

For more information on the syntax of the method, see find().

For more information on the syntax of the method, see find.

For more information on the syntax of the method, see find().

For more information on the syntax of the method, see collection.find().

Specify Equality Condition

To specify equality conditions, use <field>:<value> expressions in the query filter document:

{ <field1>: <value1>, ... }

To specify equality conditions, use <field>:<value> expressions in the query filter document:

{ <field1>: <value1>, ... }

To specify equality conditions, use <field>:<value> expressions in the query filter document:

{ <field1>: <value1>, ... }

To specify equality conditions, construct a filter using the Eq method:

Builders<BsonDocument>.Filter.Eq(<field>, <value>);

To specify equality conditions, use the com.mongodb.client.model.Filters.eq method to create the query filter document:

and(eq(<field1>, <value1>), eq(<field2>, <value2>) ...)

To specify equality conditions, use the com.mongodb.client.model.Filters.eq_ method to create the query filter document:

and(eq(<field1>, <value1>), eq(<field2>, <value2>) ...)

To specify equality conditions, use the Filters.eq() method to create the query filter document:

and(eq(<field1>, <value1>), eq(<field2>, <value2>) ...)

To specify equality conditions, use <field>:<value> expressions in the query filter document:

{ <field1>: <value1>, ... }

To specify equality conditions, use <field>:<value> expressions in the query filter document:

{ <field1>: <value1>, ... }

To specify equality conditions, use <field> => <value> expressions in the query filter document:

{ <field1> => <value1>, ... }

To specify equality conditions, use <field> => <value> expressions in the query filter document:

[ <field1> => <value1>, ... ]

To specify equality conditions, use <field>:<value> expressions in the query filter document:

{ <field1>: <value1>, ... }

To specify equality conditions, use <field> => <value> expressions in the query filter document:

{ <field1> => <value1>, ... }

To specify equality conditions, use the com.mongodb.client.model.Filters.eq_ method to create the query filter document:

and(equal(<field1>, <value1>), equal(<field2>, <value2>) ...)

The following example selects from the inventory collection all documents where the status equals "D":

db.inventory.find( { status: "D" } )

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

{ status: "D" }

mongoc_collection_t *collection;
bson_t *filter;
mongoc_cursor_t *cursor;
collection = mongoc_database_get_collection (db, "inventory");
filter = BCON_NEW ("status", BCON_UTF8 ("D"));
cursor = mongoc_collection_find_with_opts (collection, filter, NULL, NULL);

var filter = Builders<BsonDocument>.Filter.Eq("status", "D");
var result = collection.Find(filter).ToList();

cursor, err := coll.Find(
	context.TODO(),
	bson.D{{"status", "D"}},
)

findPublisher = collection.find(eq("status", "D"));

findIterable = collection.find(eq("status", "D"));

val findFlow = collection
    .find(eq("status", "D"))

cursor = db.inventory.find({"status": "D"})

const cursor = db.collection('inventory').find({ status: 'D' });

$cursor = $db->coll("inventory")->find( { status => "D" } );

$cursor = $db->inventory->find(['status' => 'D']);

cursor = db.inventory.find({"status": "D"})

client[:inventory].find(status: 'D')

findObservable = collection.find(equal("status", "D"))

This operation uses a query predicate of { status: "D" }, which corresponds to the following SQL statement:

SELECT * FROM inventory WHERE status = "D"

Note

The MongoDB Compass query bar autocompletes the current query based on the keys in your collection's documents, including keys in embedded sub-documents.

Specify Conditions Using Query Operators

A query filter document can use the query operators to specify conditions in the following form:

{ <field1>: { <operator1>: <value1> }, ... }

A query filter document can use the query operators to specify conditions in the following form:

{ <field1>: { <operator1>: <value1> }, ... }

A query filter document can use the query operators to specify conditions in the following form:

{ <field1>: { <operator1>: <value1> }, ... }

In addition to the equality filter, MongoDB provides various query operators to specify filter conditions. Use the FilterDefinitionBuilder methods to create a filter document. For example:

var builder = Builders<BsonDocument>.Filter;
builder.And(builder.Eq(<field1>, <value1>), builder.Lt(<field2>, <value2>));

In addition to the equality condition, MongoDB provides various query operators to specify filter conditions. Use the com.mongodb.client.model.Filters helper methods to facilitate the creation of filter documents. For example:

and(gte(<field1>, <value1>), lt(<field2>, <value2>), eq(<field3>, <value3>))

In addition to the equality condition, MongoDB provides various query operators to specify filter conditions. Use the com.mongodb.client.model.Filters helper methods to facilitate the creation of filter documents. For example:

and(gte(<field1>, <value1>), lt(<field2>, <value2>), eq(<field3>, <value3>))

In addition to the equality condition, MongoDB provides various query operators to specify filter conditions. Use the com.mongodb.client.model.Filters helper methods to facilitate the creation of filter documents. For example:

and(gte(<field1>, <value1>), lt(<field2>, <value2>), eq(<field3>, <value3>))

A query filter document can use the query operators to specify conditions in the following form:

{ <field1>: { <operator1>: <value1> }, ... }

A query filter document can use the query operators to specify conditions in the following form:

{ <field1>: { <operator1>: <value1> }, ... }

A query filter document can use the query operators to specify conditions in the following form:

{ <field1> => { <operator1> => <value1> }, ... }

A query filter document can use the query operators to specify conditions in the following form:

[ <field1> => [ <operator1> => <value1> ], ... ]

A query filter document can use the query operators to specify conditions in the following form:

{ <field1>: { <operator1>: <value1> }, ... }

A query filter document can use the query operators to specify conditions in the following form:

{ <field1> => { <operator1> => <value1> }, ... }

In addition to the equality condition, MongoDB provides various query operators to specify filter conditions. Use the com.mongodb.client.model.Filters_ helper methods to facilitate the creation of filter documents. For example:

and(gte(<field1>, <value1>), lt(<field2>, <value2>), equal(<field3>, <value3>))

The following example retrieves all documents from the inventory collection where status equals either "A" or "D":

db.inventory.find( { status: { $in: [ "A", "D" ] } } )

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

{ status: { $in: [ "A", "D" ] } }

mongoc_collection_t *collection;
bson_t *filter;
mongoc_cursor_t *cursor;
collection = mongoc_database_get_collection (db, "inventory");
filter = BCON_NEW (
   "status", "{",
   "$in", "[",
   BCON_UTF8 ("A"), BCON_UTF8 ("D"),
   "]",
   "}");
cursor = mongoc_collection_find_with_opts (collection, filter, NULL, NULL);

var filter = Builders<BsonDocument>.Filter.In("status", new[] { "A", "D" });
var result = collection.Find(filter).ToList();

cursor, err := coll.Find(
	context.TODO(),
	bson.D{{"status", bson.D{{"$in", bson.A{"A", "D"}}}}})

findPublisher = collection.find(in("status", "A", "D"));

findIterable = collection.find(in("status", "A", "D"));

val findFlow = collection
    .find(`in`("status", "A", "D"))

cursor = db.inventory.find({"status": {"$in": ["A", "D"]}})

const cursor = db.collection('inventory').find({
  status: { $in: ['A', 'D'] }
});

$cursor = $db->coll("inventory")->find( { status => { '$in' => [ "A", "D" ] } } );

$cursor = $db->inventory->find(['status' => ['$in' => ['A', 'D']]]);

cursor = db.inventory.find({"status": {"$in": ["A", "D"]}})

client[:inventory].find(status: { '$in' => [ 'A', 'D' ]})

findObservable = collection.find(in("status", "A", "D"))

Note

Although you can express this query using the $or operator, use the $in operator rather than the $or operator when performing equality checks on the same field.

The operation uses a query predicate of { status: { $in: [ "A", "D" ] } }, which corresponds to the following SQL statement:

SELECT * FROM inventory WHERE status in ("A", "D")

Refer to the Query and Projection Operators document for the complete list of MongoDB query operators.

Specify `AND` Conditions

A compound query can specify conditions for more than one field in the collection's documents. Implicitly, a logical AND conjunction connects the clauses of a compound query so that the query selects the documents in the collection that match all the conditions.

The following example retrieves all documents in the inventory collection where the status equals "A" and qty is less than ($lt) 30:

db.inventory.find( { status: "A", qty: { $lt: 30 } } )

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

{ status: "A", qty: { $lt: 30 } }

mongoc_collection_t *collection;
bson_t *filter;
mongoc_cursor_t *cursor;
collection = mongoc_database_get_collection (db, "inventory");
filter = BCON_NEW (
   "status", BCON_UTF8 ("A"),
   "qty", "{",
   "$lt", BCON_INT64 (30),
   "}");
cursor = mongoc_collection_find_with_opts (collection, filter, NULL, NULL);

var builder = Builders<BsonDocument>.Filter;
var filter = builder.And(builder.Eq("status", "A"), builder.Lt("qty", 30));
var result = collection.Find(filter).ToList();

cursor, err := coll.Find(
	context.TODO(),
	bson.D{
		{"status", "A"},
		{"qty", bson.D{{"$lt", 30}}},
	})

findPublisher = collection.find(and(eq("status", "A"), lt("qty", 30)));

findIterable = collection.find(and(eq("status", "A"), lt("qty", 30)));

val findFlow = collection
    .find(and(eq("status", "A"), lt("qty", 30)))

cursor = db.inventory.find({"status": "A", "qty": {"$lt": 30}})

const cursor = db.collection('inventory').find({
  status: 'A',
  qty: { $lt: 30 }
});

$cursor = $db->coll("inventory")->find( { status => "A", qty => { '$lt' => 30 } } );

$cursor = $db->inventory->find([
    'status' => 'A',
    'qty' => ['$lt' => 30],
]);

cursor = db.inventory.find({"status": "A", "qty": {"$lt": 30}})

client[:inventory].find(status: 'A', qty: { '$lt' => 30 })

findObservable = collection.find(and(equal("status", "A"), lt("qty", 30)))

The operation uses a query predicate of { status: "A", qty: { $lt: 30 } }, which corresponds to the following SQL statement:

SELECT * FROM inventory WHERE status = "A" AND qty < 30

See comparison operators for other MongoDB comparison operators.

Specify `OR` Conditions

Using the $or operator, you can specify a compound query that joins each clause with a logical OR conjunction so that the query selects the documents in the collection that match at least one condition.

The following example retrieves all documents in the collection where the status equals "A" or qty is less than ($lt) 30:

db.inventory.find( { $or: [ { status: "A" }, { qty: { $lt: 30 } } ] } )

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

{ $or: [ { status: "A" }, { qty: { $lt: 30 } } ] }

mongoc_collection_t *collection;
bson_t *filter;
mongoc_cursor_t *cursor;
collection = mongoc_database_get_collection (db, "inventory");
filter = BCON_NEW (
   "$or", "[",
   "{",
   "status", BCON_UTF8 ("A"),
   "}","{",
   "qty", "{",
   "$lt", BCON_INT64 (30),
   "}",
   "}",
   "]");
cursor = mongoc_collection_find_with_opts (collection, filter, NULL, NULL);

var builder = Builders<BsonDocument>.Filter;
var filter = builder.Or(builder.Eq("status", "A"), builder.Lt("qty", 30));
var result = collection.Find(filter).ToList();

cursor, err := coll.Find(
	context.TODO(),
	bson.D{
		{"$or",
			bson.A{
				bson.D{{"status", "A"}},
				bson.D{{"qty", bson.D{{"$lt", 30}}}},
			}},
	})

findPublisher = collection.find(or(eq("status", "A"), lt("qty", 30)));

findIterable = collection.find(or(eq("status", "A"), lt("qty", 30)));

val findFlow = collection
    .find(or(eq("status", "A"), lt("qty", 30)))

cursor = db.inventory.find({"$or": [{"status": "A"}, {"qty": {"$lt": 30}}]})

const cursor = db.collection('inventory').find({
  $or: [{ status: 'A' }, { qty: { $lt: 30 } }]
});

$cursor = $db->coll("inventory")->find(
    { '$or' => [ { status => "A" }, { qty => { '$lt' => 30 } } ] }
);

$cursor = $db->inventory->find([
    '$or' => [
        ['status' => 'A'],
        ['qty' => ['$lt' => 30]],
    ],
]);

cursor = db.inventory.find({"$or": [{"status": "A"}, {"qty": {"$lt": 30}}]})

client[:inventory].find('$or' => [{ status: 'A' },
                                  { qty: { '$lt' => 30 } }
                                 ])

findObservable = collection.find(or(equal("status", "A"), lt("qty", 30)))

The operation uses a query predicate of { $or: [ { status: 'A' }, { qty: { $lt: 30 } } ] }, which corresponds to the following SQL statement:

SELECT * FROM inventory WHERE status = "A" OR qty < 30

Note

Queries that use comparison operators are subject to Type Bracketing.

Specify `AND` as well as `OR` Conditions

In the following example, the compound query document selects all documents in the collection where the status equals "A" and either qty is less than ($lt) 30 or item starts with the character p:

db.inventory.find( {
     status: "A",
     $or: [ { qty: { $lt: 30 } }, { item: /^p/ } ]
} )

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

{ status: "A", $or: [ { qty: { $lt: 30 } }, { item: /^p/ } ] }

mongoc_collection_t *collection;
bson_t *filter;
mongoc_cursor_t *cursor;
collection = mongoc_database_get_collection (db, "inventory");
filter = BCON_NEW (
   "status", BCON_UTF8 ("A"),
   "$or", "[",
   "{",
   "qty", "{",
   "$lt", BCON_INT64 (30),
   "}",
   "}","{",
   "item", BCON_REGEX ("^p", ""),
   "}",
   "]");
cursor = mongoc_collection_find_with_opts (collection, filter, NULL, NULL);

var builder = Builders<BsonDocument>.Filter;
var filter = builder.And(
    builder.Eq("status", "A"),
    builder.Or(builder.Lt("qty", 30), builder.Regex("item", new BsonRegularExpression("^p"))));
var result = collection.Find(filter).ToList();

cursor, err := coll.Find(
	context.TODO(),
	bson.D{
		{"status", "A"},
		{"$or", bson.A{
			bson.D{{"qty", bson.D{{"$lt", 30}}}},
			bson.D{{"item", bson.Regex{Pattern: "^p", Options: ""}}},
		}},
	})

findPublisher = collection.find(
        and(eq("status", "A"),
                or(lt("qty", 30), regex("item", "^p")))
);

findIterable = collection.find(
        and(eq("status", "A"),
                or(lt("qty", 30), regex("item", "^p")))
);

val findFlow = collection
    .find(
        and(eq("status", "A"),
            or(lt("qty", 30), regex("item", "^p")))
    )

cursor = db.inventory.find(
    {"status": "A", "$or": [{"qty": {"$lt": 30}}, {"item": {"$regex": "^p"}}]}
)

const cursor = db.collection('inventory').find({
  status: 'A',
  $or: [{ qty: { $lt: 30 } }, { item: { $regex: '^p' } }]
});

$cursor = $db->coll("inventory")->find(
    {
        status => "A",
        '$or'  => [ { qty => { '$lt' => 30 } }, { item => { '$regex' => "^p" } } ]
    }
);

$cursor = $db->inventory->find([
    'status' => 'A',
    '$or' => [
        ['qty' => ['$lt' => 30]],
        // Alternatively: ['item' => new \MongoDB\BSON\Regex('^p')]
        ['item' => ['$regex' => '^p']],
    ],
]);

cursor = db.inventory.find(
    {"status": "A", "$or": [{"qty": {"$lt": 30}}, {"item": {"$regex": "^p"}}]}
)

client[:inventory].find(status: 'A',
                        '$or' => [{ qty: { '$lt' => 30 } },
                                  { item: { '$regex' => BSON::Regexp::Raw.new('^p') } }
                        ])

findObservable = collection.find(and(
  equal("status", "A"),
  or(lt("qty", 30), regex("item", "^p")))
)

The operation uses a query predicate of:

{
   status: 'A',
   $or: [
     { qty: { $lt: 30 } }, { item: { $regex: '^p' } }
   ]
}

which corresponds to the following SQL statement:

SELECT * FROM inventory WHERE status = "A" AND ( qty < 30 OR item LIKE "p%")

Note

MongoDB supports regular expressions $regex queries to perform string pattern matches.

Query Documents with MongoDB Atlas

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

To project fields to return from a query in MongoDB Atlas, follow these steps:

1

In the MongoDB Atlas UI, go to the Clusters page for your project.

If it's not already displayed, select the organization that contains your desired project from the Organizations menu in the navigation bar.
If it's not already displayed, select your project from the Projects menu in the navigation bar.
If it's not already displayed, click Clusters in the sidebar.
The Clusters page displays.

2

Navigate to the collection

For the cluster that contains the sample data, click Browse Collections.
In the left navigation pane, select the sample_mflix database.
Select the movies collection.

3

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:

{ year: 1924 }

4

Click Apply

This query filter returns all documents in the sample_mflix.movies collection where the year field matches 1924.

Additional Query Tutorials

For additional query examples, see:

Behavior

Cursor

The db.collection.find() method returns a cursor to the matching documents.

The MongoDB Compass Find operation opens a cursor to the matching documents of the collection based on the find query.

For more information on sampling in MongoDB Compass, see the Compass FAQ.

The mongoc_collection_find method returns a cursor to the matching documents.

The MongoCollection.Find() method returns a cursor to the matching documents. See the MongoDB C# driver documentation for iterating over a cursor.

The Collection.Find function returns a Cursor to the matching documents. See the Cursor documentation for more information.

com.mongodb.reactivestreams.client.MongoCollection.find returns an instance of the com.mongodb.reactivestreams.client.FindPublisher interface.

The com.mongodb.client.MongoCollection.find method returns an instance of the com.mongodb.client.FindIterable interface.

The MongoCollection.find() method returns an instance of the FindFlow class.

The Collection.find() method returns a cursor.

The MongoDB\\Collection::find() method returns a cursor to the matching documents. See the MongoDB PHP Library documentation for iterating over a cursor.

The pymongo.collection.Collection.find method returns a cursor to the matching documents. See the PyMongo documentation for iterating over a cursor.

The Mongo::Collection#find() method returns a CollectionView, which is an Enumerable. A Cursor is created when the View is enumerated; for example, by calling #to_a() or #each(). You can also get an Enumerator by calling #to_enum() on the View. See the Ruby driver API documentation for iterating over a cursor.

The collection.find() method returns the find Observable.

Read Isolation

For reads to Replica sets and replica set shards, read concern allows clients to choose a level of isolation for their reads. For more information, see Read Concern.

Query Result Format

When you run a find operation with a MongoDB driver or mongosh, the command returns a cursor that manages query results. The query results are not returned as an array of documents.

To learn how to iterate through documents in a cursor, refer to your driver's documentation. If you are using mongosh, see Iterate a Cursor in mongosh.

Additional Methods and Options

The following can also read documents from a collection:

The db.collection.findOne() method
The $match pipeline stage in an aggregation pipeline. The $match pipeline stage provides access to MongoDB queries

Note

The db.collection.findOne() method performs the same operation as the db.collection.find() method with a limit of 1.

In addition to filter, MongoDB Compass also allows you to pass the following options to the query bar:

Project	Specify which fields to return in the resulting data.
Sort	Specify the sort order of the returned documents.
Skip	Specify the first n-number of document to skip before returning the result set.
Limit	Specify the maximum number of documents to return.

The following method can also read documents from a collection:

mongoc_find_and_modify_opts_t

The following can also read documents from a collection:

MongoCollection.FindOne()
In aggregation pipeline, the $match pipeline stage provides access to MongoDB queries. See the MongoDB C# driver's LINQ documentation.

Note

The MongoCollection.FindOne() method performs the same operation as the MongoCollection.Find() method with a limit of 1.

The following can also read documents from a collection:

Collection.FindOne
In aggregation pipeline, the $match pipeline stage provides access to MongoDB queries. See Collection.Aggregate.

The following can also read documents from a collection:

In the aggregation pipeline, the $match pipeline stage provides access to MongoDB queries. See the Java Synchronous Driver Aggregation Examples.

The following methods can also read documents from a collection:

In an aggregation pipeline, the $match pipeline stage allows you to perform MongoDB queries. See the Kotlin Coroutine Driver Find Operation Examples to learn more.

The following can also read documents from a collection:

Collection.findOne()
In aggregation pipeline, the $match pipeline stage provides access to MongoDB queries. See the MongoDB Node.js Driver's aggregation tutorial.

Note

The Collection.findOne() method performs the same operation as the Collection.find() method with a limit of 1.

The following can also read documents from a collection:

MongoDB\\Collection::findOne()
In aggregation pipeline, the $match pipeline stage provides access to MongoDB queries. See the MongoDB PHP Library's aggregation example.

Note

The MongoDB\\Collection::findOne() method performs the same operation as the MongoDB\\Collection::find() method with a limit of 1.

The following can also read documents from a collection:

pymongo.collection.Collection.find_one
In an aggregation pipeline, the $match pipeline stage provides access to MongoDB queries. See the PyMongo Aggregation Examples.

Note

The pymongo.collection.Collection.find_one method performs the same operation as the the pymongo.collection.Collection.find method with a limit of 1.

The following can also read documents from a collection:

In aggregation pipeline, the $match pipeline stage provides access to MongoDB queries. See the MongoDB Ruby driver's aggregation examples.

The following can also read documents from a collection:

In aggregation pipeline, the $match pipeline stage provides access to MongoDB queries. See the MongoDB Scala driver's aggregate method.

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On this page

Select All Documents in a Collection
Specify Equality Condition
Specify Conditions Using Query Operators
Specify AND Conditions
Specify OR Conditions
Specify AND as well as OR Conditions
Query Documents with MongoDB Atlas
Additional Query Tutorials
Behavior
Additional Methods and Options