Step 1: Switch to the Database

Before inserting data, ensure you're in the correct database. If the database doesn't exist, MongoDB will create it automatically when inserting data.

use myDatabase

Step 2: Insert a Single Document

To insert a single document into a collection, use insertOne(). If the collection doesn't exist, MongoDB creates it automatically.

db.users.insertOne({
   name: "John Doe",
   age: 30,
   city: "New York"
})

✅ MongoDB automatically assigns a unique _id field to each document.

Step 3: Insert Multiple Documents

To insert multiple documents at once, use insertMany().

db.users.insertMany([
   { name: "Alice", age: 25, city: "London" },
   { name: "Bob", age: 28, city: "Toronto" },
   { name: "Charlie", age: 32, city: "Sydney" }
])

✅ All documents are stored in the users collection.

Step 4: Verify Inserted Data

To check if the data was inserted correctly, use the find() command:

db.users.find()

For a more readable output:

db.users.find().pretty()

Step 5: Insert Data with Custom _id

You can define a custom _id field instead of the default one generated by MongoDB.

db.users.insertOne({
   _id: 101,
   name: "David",
   age: 29,
   city: "Berlin"
})

✅ Ensure _id values are unique to avoid errors.

Step 6: Handling Insert Errors

• If you try inserting a document with an _id that already exists, MongoDB will throw an error.
• insertMany() allows you to use { ordered: false } to continue inserting even if some documents fail.

db.users.insertMany([
   { _id: 102, name: "Emma", age: 27, city: "Paris" },
   { _id: 102, name: "Oliver", age: 30, city: "Madrid" }
], { ordered: false })

✅ The second document will fail, but the first will still be inserted.

Conclusion

You’ve now learned how to insert data into MongoDB collections. Here’s a quick recap:
✅ Use insertOne() for inserting a single document.
✅ Use insertMany() for inserting multiple documents.
✅ Verify inserted data using find().
✅ Handle errors with ordered inserts.

Now you're ready to start managing your data efficiently in MongoDB! 🚀