DEV Community

Cover image for 💻 Common MongoDB Commands 🌱
Truong Phung
Truong Phung

Posted on

💻 Common MongoDB Commands 🌱

#webdev #mongodb #cli #tutorial

Here’s a comprehensive example that covers many common MongoDB features (Quick Setup). I'll showcase operations like document creation, querying, indexing, aggregation, and more, based on a hypothetical e-commerce database structure.

Use Case: E-Commerce Database

We will use a database called ecommerce, which contains collections like users, products, orders, and reviews.

1. Database Setup 

use ecommerce;
Enter fullscreen mode Exit fullscreen mode

This switches to (or creates) the ecommerce database.

2. Inserting Documents (CRUD)

Insert Single Document

db.users.insertOne({
    username: "johndoe",
    email: "johndoe@example.com",
    password: "hashed_password",
    createdAt: new Date()
});
Enter fullscreen mode Exit fullscreen mode

Insert Multiple Documents

db.products.insertMany([
    {
        name: "Laptop",
        description: "A high-end gaming laptop.",
        price: 1500,
        stock: 30,
        categories: ["electronics", "gaming"],
        ratings: []
    },
    {
        name: "Smartphone",
        description: "A latest model smartphone.",
        price: 800,
        stock: 50,
        categories: ["electronics", "mobile"],
        ratings: []
    }
]);
Enter fullscreen mode Exit fullscreen mode

3. Querying Documents

Find All Documents

db.products.find({});
Enter fullscreen mode Exit fullscreen mode

Find with Conditions

db.products.find({
    price: { $gt: 1000 },
    categories: "electronics"
});
Enter fullscreen mode Exit fullscreen mode

Find Specific Fields (Projections)

db.products.find(
    { price: { $gt: 1000 } },
    { name: 1, price: 1, _id: 0 }
);
Enter fullscreen mode Exit fullscreen mode

Sorting and Limiting Results

db.products.find().sort({ price: -1 }).limit(5);
Enter fullscreen mode Exit fullscreen mode

4. Updating Documents

Update a Single Document

db.products.updateOne(
    { name: "Laptop" },
    { $set: { price: 1400 } }
);
Enter fullscreen mode Exit fullscreen mode

Update Multiple Documents

db.products.updateMany(
    { categories: "electronics" },
    { $inc: { stock: 10 } }
);
Enter fullscreen mode Exit fullscreen mode

Upsert (Update or Insert)

db.products.updateOne(
    { name: "Tablet" },
    {
        $set: {
            name: "Tablet",
            description: "A lightweight tablet.",
            price: 500,
            stock: 20,
            categories: ["electronics", "tablet"]
        }
    },
    { upsert: true }
);
Enter fullscreen mode Exit fullscreen mode

5. Deleting Documents

Delete a Single Document

db.products.deleteOne({ name: "Smartphone" });
Enter fullscreen mode Exit fullscreen mode

Delete Multiple Documents

db.products.deleteMany({ categories: "gaming" });
Enter fullscreen mode Exit fullscreen mode

6. Indexes

Indexes are critical for performance optimization.

Create Indexes

db.products.createIndex({ name: 1 });  // Ascending index on the `name` field
db.products.createIndex({ price: -1 });  // Descending index on the `price` field
Enter fullscreen mode Exit fullscreen mode

Compound Index

db.products.createIndex({ name: 1, price: -1 });
Enter fullscreen mode Exit fullscreen mode

Text Index (For Full-Text Search)

db.products.createIndex({ description: "text", name: "text" });
Enter fullscreen mode Exit fullscreen mode

7. Full-Text Search

Using the text index created earlier, you can perform full-text searches.

db.products.find({ $text: { $search: "gaming laptop" } });
Enter fullscreen mode Exit fullscreen mode

8. Aggregation Framework

Aggregation is powerful for transforming and analyzing data.

Example: Calculate the Average Price of Products

db.products.aggregate([
    {
        $group: {
            _id: null,
            averagePrice: { $avg: "$price" }
        }
    }
]);
Enter fullscreen mode Exit fullscreen mode

Example: Products by Category

db.products.aggregate([
    {
        $unwind: "$categories"
    },
    {
        $group: {
            _id: "$categories",
            totalProducts: { $sum: 1 },
            avgPrice: { $avg: "$price" }
        }
    },
    {
        $sort: { totalProducts: -1 }
    }
]);
Enter fullscreen mode Exit fullscreen mode

Example: Join Collections (Using $lookup)

db.orders.aggregate([
    {
        $lookup: {
            from: "users",
            localField: "user_id",
            foreignField: "_id",
            as: "user_details"
        }
    }
]);
Enter fullscreen mode Exit fullscreen mode

9. Transactions

Starting with MongoDB 4.0, multi-document transactions are supported for replica sets.

const session = db.getMongo().startSession();
session.startTransaction();

try {
    db.products.updateOne(
        { name: "Laptop" },
        { $inc: { stock: -1 } },
        { session }
    );

    db.orders.insertOne(
        {
            product_id: ObjectId("..."),
            user_id: ObjectId("..."),
            quantity: 1,
            totalPrice: 1500,
            createdAt: new Date()
        },
        { session }
    );

    session.commitTransaction();
} catch (e) {
    session.abortTransaction();
} finally {
    session.endSession();
}
Enter fullscreen mode Exit fullscreen mode

10. Geospatial Queries

If your data includes geographical coordinates, you can perform spatial queries.

Create a Geospatial Index

db.stores.createIndex({ location: "2dsphere" });
Enter fullscreen mode Exit fullscreen mode

Find Stores Near a Coordinate

db.stores.find({
    location: {
        $near: {
            $geometry: { type: "Point", coordinates: [-73.97, 40.77] },
            $maxDistance: 5000  // meters
        }
    }
});
Enter fullscreen mode Exit fullscreen mode

11. Handling Large Documents (GridFS)

For storing large files like images or videos, MongoDB provides GridFS. Here's how you can interact with it:

Storing a File in GridFS

var bucket = new mongoose.mongo.GridFSBucket(db, {
    bucketName: 'myFiles'
});
bucket.openUploadStream("myImage.jpg").end("image_binary_data");
Enter fullscreen mode Exit fullscreen mode

Reading a File from GridFS

bucket.openDownloadStreamByName("myImage.jpg").pipe(fs.createWriteStream("./myImage.jpg"));
Enter fullscreen mode Exit fullscreen mode

12. Schema Validation

You can enforce some schema validation rules on your collections.

Example: Enforce Price to Be a Positive Number

db.createCollection("products", {
    validator: {
        $jsonSchema: {
            bsonType: "object",
            required: ["name", "price", "stock"],
            properties: {
                price: {
                    bsonType: "double",
                    minimum: 0,
                    description: "Price must be a positive number"
                },
                stock: {
                    bsonType: "int",
                    minimum: 0,
                    description: "Stock must be a non-negative integer"
                }
            }
        }
    }
});
Enter fullscreen mode Exit fullscreen mode

13. Role-Based Access Control (RBAC)

MongoDB supports fine-grained control over database user permissions.

Create a User with Read-Only Access to the ecommerce Database

db.createUser({
    user: "readonly_user",
    pwd: "password",
    roles: [{ role: "read", db: "ecommerce" }]
});
Enter fullscreen mode Exit fullscreen mode

Create a User with Full Access

db.createUser({
    user: "admin_user",
    pwd: "securepassword",
    roles: [{ role: "dbOwner", db: "ecommerce" }]
});
Enter fullscreen mode Exit fullscreen mode

14. Sharding (For Scalability)

MongoDB allows horizontal scaling through sharding. This example assumes a sharded cluster is already set up.

Enable Sharding on a Database

sh.enableSharding("ecommerce");
Enter fullscreen mode Exit fullscreen mode

Shard a Collection

sh.shardCollection("ecommerce.products", { product_id: "hashed" });
Enter fullscreen mode Exit fullscreen mode

15. Explain Command

The explain command is used to understand how MongoDB processes queries. It provides insights into the query plan, index usage, and performance metrics

Example: Using explain for Query Optimization

db.products.find({ price: { $gt: 1000 } }).explain("executionStats");
Enter fullscreen mode Exit fullscreen mode

This will return detailed statistics on how the query is executed, including whether an index was used, the number of documents examined, and the time taken.

16. Change Streams

MongoDB supports Change Streams, which allow applications to listen for real-time changes to a collection, database, or even across an entire cluster.

Example: Watching Changes in a Collection

const changeStream = db.products.watch();
changeStream.on("change", (next) => {
    console.log("Change detected:", next);
});
Enter fullscreen mode Exit fullscreen mode

This is particularly useful for real-time applications where you need to monitor data updates.

17. TTL Index (Time to Live)

TTL indexes allow you to automatically remove documents after a certain period.

Example: Set a TTL Index for Expiring Documents

db.sessions.createIndex({ createdAt: 1 }, { expireAfterSeconds: 3600 });
Enter fullscreen mode Exit fullscreen mode

In this case, any document in the sessions collection will be automatically removed 1 hour (3600 seconds) after its createdAt timestamp.

18. Partial Indexes

Partial indexes are useful when you want to index a subset of documents in a collection, improving performance and reducing storage costs.

Example: Create a Partial Index

db.products.createIndex({ price: 1 }, { partialFilterExpression: { price: { $gt: 1000 } } });
Enter fullscreen mode Exit fullscreen mode

This index will only be created for products with a price greater than 1000.

19. WildCard Indexes

WildCard indexes can be used when you need to create an index on all fields of a document, useful for semi-structured data.

Example: Create a WildCard Index

db.products.createIndex({ "$**": 1 });
Enter fullscreen mode Exit fullscreen mode

This will index all fields and subfields of documents in the products collection.

20. Hidden Indexes

Hidden indexes allow you to create indexes that MongoDB does not automatically consider during query execution, useful for testing purposes.

Example: Create and Hide an Index

db.products.createIndex({ name: 1 }, { hidden: true });
Enter fullscreen mode Exit fullscreen mode

This creates an index on name, but MongoDB will not use it for queries unless explicitly told.

21. Collations (for String Comparisons)

Collations allow you to specify language-specific rules for string comparisons, such as case-sensitivity and accent marks.

Example: Create a Collection with Case-Insensitive Collation

db.products.createIndex({ name: 1 }, { collation: { locale: "en", strength: 2 } });
Enter fullscreen mode Exit fullscreen mode

This makes the name field in the index case-insensitive for English.

22. Field-Level Encryption (FLE)

MongoDB supports Field-Level Encryption (FLE), allowing sensitive data to be encrypted at the field level.

Example: Encrypting a Field

const encryptedField = clientEncryption.encrypt("sensitive_data", {
    keyId: encryptionKeyId,
    algorithm: "AEAD_AES_256_CBC_HMAC_SHA_512-Deterministic"
});

db.users.insertOne({
    name: "John Doe",
    email: "johndoe@example.com",
    password: encryptedField
});
Enter fullscreen mode Exit fullscreen mode

23. Replication

While sharding focuses on horizontal scaling, replication is designed for fault tolerance and high availability. MongoDB supports automatic failover with replica sets.

Example: Initiating a Replica Set

rs.initiate({
    _id: "rs0",
    members: [
        { _id: 0, host: "localhost:27017" },
        { _id: 1, host: "localhost:27018" },
        { _id: 2, host: "localhost:27019" }
    ]
});
Enter fullscreen mode Exit fullscreen mode

24. Concurrency Control (Optimistic Locking)

MongoDB doesn’t lock records like relational databases but allows for optimistic concurrency control via the use of a version field (for example).

Example: Optimistic Locking with version Field

db.orders.updateOne(
    { _id: ObjectId("..."), version: 1 },
    { $set: { status: "shipped" }, $inc: { version: 1 } }
);
Enter fullscreen mode Exit fullscreen mode

The update will only succeed if the document's version is 1, preventing race conditions in concurrent updates.

25. MongoDB Atlas (Cloud Features)

MongoDB Atlas is the fully managed cloud version of MongoDB. It includes features like:

  • Performance Advisor: Suggests indexes based on query patterns.
  • Backup & Restore: Automated backups and point-in-time recovery.
  • Global Clusters: Distribute data across multiple geographic regions for faster access.

Example: Setting Up Global Clusters in Atlas

In Atlas, you can define zones for data distribution across different regions. For example, store European users' data in the EU, and American users' data in the US.

Conclusion

This example provides a thorough introduction to many common MongoDB features:

  • CRUD operations (insert, find, update, delete)
  • Indexing (single-field, compound, text)
  • Aggregation (grouping, joining)
  • Transactions (multi-document)
  • Full-text search
  • Schema validation
  • Geospatial queries
  • GridFS for large files
  • Role-based access control
  • Sharding
  • Explain command for query optimization.
  • Real-time change streams.
  • TTL indexes for expiring data.
  • Partial and wildcard indexes.
  • Hidden indexes for testing.
  • Collations for string comparisons.
  • Field-level encryption for sensitive data.
  • Replication for fault tolerance.
  • Optimistic locking for concurrency control.
  • Atlas-specific cloud features like backups and global clusters.

Each of these operations is essential for building efficient, scalable applications with MongoDB.

If you found this helpful, let me know by leaving a 👍 or a comment!, or if you think this post could help someone, feel free to share it! Thank you very much! 😃

Top comments (0)

Read next

babar_ali profile image

Blur Card Effect

babar ali -

angelaswift profile image

Software for MacOS Developers that cannot Miss, Once More

Angela Swift -

deni_sugiarto_1a01ad7c3fb profile image

Fixing “Connection Refused” Error Between pgAdmin and Postgres in Docker

Deni Sugiarto -

aleflewitt profile image

Bootcamping 01: An Unexpected Behavior of Mongoose

Alef Lewitt -