Retrieve Data
Overview
You can perform find operations to retrieve data from your MongoDB database.
You can perform a find operation to match documents on a set of criteria
by calling the find()
or findOne()
method.
Tip
Interactive Lab
This page includes a short interactive lab that demonstrates how to
retrieve data by using the find()
method. You can complete this lab
directly in your browser window without installing MongoDB or a code editor.
To start the lab, click the Open Interactive Tutorial button at the top of the page. To expand the lab to a full-screen format, click the full-screen button (⛶) in the top-right corner of the lab pane.
You can also further specify the information that the find operation returns by specifying optional parameters or by chaining other methods, as shown in the following guides:
You can also use an aggregation operation to retrieve data. This type of operation allows you to apply an ordered pipeline of transformations to the matched data.
If you want to monitor the database for incoming data that matches a set of criteria, you can use the watch operation to be notified in real-time when matching data is inserted.
Note
Your query operation may return a reference to a cursor that contains matching documents. To learn how to examine data stored in the cursor, see the Cursor Fundamentals page.
You can use the Node.js driver to connect and perform read operations for deployments hosted in the following environments:
MongoDB Atlas: The fully managed service for MongoDB deployments in the cloud
MongoDB Enterprise: The subscription-based, self-managed version of MongoDB
MongoDB Community: The source-available, free-to-use, and self-managed version of MongoDB
To learn more about performing read operations in the Atlas UI for deployments hosted in MongoDB Atlas, see View, Filter, and Sort Documents.
Find Documents
You can call the find()
method on a Collection
object. The
method accepts a query document that describes the documents you want to
retrieve. For more information on how to specify your query document,
see the Specify a Query guide.
Tip
No Query Criteria
To execute a find operation that has no query criteria, you can pass an empty query or omit the query document in your find method parameters.
The following operations both return all documents in the
myColl
collection:
await myColl.find(); // no query await myColl.find({}); // empty query
If you don't pass a query or pass an empty query
to the findOne()
method, the operation returns a single
document from a collection.
You can specify options in a find operation even when you pass an empty query. For example, the following code shows how you can specify a projection as an option while executing a find operation with an empty query parameter:
const options = { projection: { _id: 0, field1: 1 }, }; const findResult = await myColl.findOne({}, options);
If you resolve the Promise
returned by find()
, you receive
a reference to a Cursor
with which you can navigate matched documents.
If you resolve the Promise
returned by findOne()
, you receive the
matching document or null
if there are no matches.
Example
A pizza restaurant wants to find all pizzas ordered by Lemony Snicket
yesterday. They run the following find()
query on the
orders
collection:
const findResult = await orders.find({ name: "Lemony Snicket", date: { $gte: new Date(new Date().setHours(00, 00, 00)), $lt: new Date(new Date().setHours(23, 59, 59)), }, });
Once the operation returns, the findResult
variable references a
Cursor
. You can print the documents retrieved using the forEach()
method as shown below:
await findResult.forEach(console.dir);
The output might resemble the following:
[ { name: "Lemony Snicket", type: "horseradish pizza", qty: 1, status: "delivered", date: ... }, { name: "Lemony Snicket", type: "coal-fired oven pizza", qty: 3, status: "canceled", date: ...}, ... ]
Aggregate Data from Documents
If you want to run a custom processing pipeline to retrieve data from your
database, you can use the aggregate()
method. This method accepts
aggregation expressions to run in sequence. These expressions let you filter,
group, and arrange the result data from a collection.
Example
A pizza restaurant wants to run a status report on-demand to
summarize pizza orders over the past week. They run the following
aggregate()
query on the orders
collection to fetch the
totals for each distinct "status" field:
const aggregateResult = await orders.aggregate([ { $match: { date: { $gte: new Date(new Date().getTime() - 1000 * 3600 * 24 * 7), $lt: new Date(), }, }, }, { $group: { _id: "$status", count: { $sum: 1, }, }, }, ]);
Once the operation returns, the aggregateResult
variable references a
Cursor
. You can print the documents retrieved using the forEach()
method as shown below:
await aggregateResult.forEach(console.dir);
The output might resemble the following:
[ { _id: 'delivering', count: 5 }, { _id: 'delivered', count: 37 }, { _id: 'created', count: 9 } ]
See the MongoDB server manual pages on aggregation for more information on how to construct an aggregation pipeline.
Monitor Data Changes
You can use the watch()
method to monitor a collection for changes to
a collection that match certain criteria. These changes include inserted,
updated, replaced, and deleted documents. You can pass this method
a pipeline of aggregation commands that sequentially runs on the changed
data whenever write operations are executed on the collection.
Example
A pizza restaurant wants to receive a notification whenever a new pizza
order comes in. To accomplish this, they create an aggregation pipeline
to filter on insert operations and return specific fields. They pass
this pipeline to the watch()
method called on the orders
collection as shown below:
const changeStream = orders.watch([ { $match: { operationType: "insert" } }, { $project: { "fullDocument.name": 1, "fullDocument.address": 1, }, }, ]); changeStream.on("change", change => { const { name, address } = change.fullDocument; console.log(`New order for ${name} at ${address}.`); });
For a runnable example of the watch()
method using the NodeJS driver, see
the change streams usage example.