MongoDB Cheatsheet: 15 Powerful Tips You’ll Love

The MongoDB Cheatsheet is a quick reference guide to help developers master MongoDB syntax and commands. Whether you’re a beginner or an advanced developer, this cheatsheet covers CRUD, queries, indexing, aggregation, and MongoDB Atlas usage.

MongoDB Basics

MongoDB is a leading NoSQL, document-oriented database. Instead of rows and columns, it stores data in flexible BSON documents that resemble JSON. This flexibility makes it scalable and ideal for modern applications.

Example document:

{
  _id: ObjectId("61abcf12345"),
  name: "John Doe",
  age: 30,
  email: "john.doe@example.com",
  hobbies: ["reading", "coding", "hiking"]
}

{
  _id: ObjectId("61abcf12345"),
  name: "John Doe",
  age: 30,
  email: "john.doe@example.com",
  hobbies: ["reading", "coding", "hiking"]
}

MongoDB collections contain documents, and unlike relational databases, fields do not need a strict schema, offering greater adaptability.

CRUD Operations in MongoDB

CRUD stands for Create, Read, Update, Delete. These are the fundamental operations for any database.

Create: Insert a new document into a collection.

db.users.insertOne({ name: "Alice", age: 25 });

db.users.insertOne({ name: "Alice", age: 25 });

Read: Query documents using conditions.

db.users.find({ age: { $gt: 20 } });

db.users.find({ age: { $gt: 20 } });

Update: Modify existing data.

db.users.updateOne({ name: "Alice" }, { $set: { age: 26 } });

db.users.updateOne({ name: "Alice" }, { $set: { age: 26 } });

Delete: Remove documents.

db.users.deleteOne({ name: "Alice" });

db.users.deleteOne({ name: "Alice" });

These commands form the core of daily MongoDB use.

Query Operators

MongoDB offers rich query operators for filtering and searching data efficiently.

Comparison Operators:

db.users.find({ age: { $gte: 25 } });

db.users.find({ age: { $gte: 25 } });

Logical Operators:

db.users.find({ $or: [{ age: { $lt: 18 } }, { age: { $gte: 65 } }] });

db.users.find({ $or: [{ age: { $lt: 18 } }, { age: { $gte: 65 } }] });

Array Operators:

db.users.find({ hobbies: { $in: ["reading", "coding"] } });

db.users.find({ hobbies: { $in: ["reading", "coding"] } });

Operators allow developers to perform advanced queries with minimal code.

Aggregation Framework

The Aggregation Framework is used for transforming and analyzing data. It works like SQL’s GROUP BY with additional features.

Example aggregation:

db.users.aggregate([
  { $group: { _id: "$age", count: { $sum: 1 } } },
  { $sort: { count: -1 } }
]);

db.users.aggregate([
  { $group: { _id: "$age", count: { $sum: 1 } } },
  { $sort: { count: -1 } }
]);

Aggregation can calculate averages, counts, or combine multiple collections, making it essential for analytics.

Indexing in MongoDB

Indexes significantly improve query performance by reducing the need for full collection scans.

Example:

db.users.createIndex({ name: 1 });

db.users.createIndex({ name: 1 });

MongoDB supports compound indexes, text indexes for search, and geospatial indexes. Always analyze queries with explain() to check index usage.

Data Modeling

Data modeling is critical in MongoDB since schema design impacts performance.

Embedding example:

{
  name: "John Doe",
  address: {
    street: "123 Main St",
    city: "New York",
    country: "USA"
  }
}

{
  name: "John Doe",
  address: {
    street: "123 Main St",
    city: "New York",
    country: "USA"
  }
}

Referencing example:

{
  userId: ObjectId("61abcde12345"),
  orderId: ObjectId("61abcde67890")
}

{
  userId: ObjectId("61abcde12345"),
  orderId: ObjectId("61abcde67890")
}

Use embedding for related data frequently accessed together and referencing for large or repeating data.

MongoDB Atlas

MongoDB Atlas is a fully managed cloud service that runs MongoDB clusters globally. It provides monitoring, backup, and auto-scaling.

Connection Example (Node.js):

const { MongoClient } = require("mongodb");
const uri = "mongodb+srv://<username>:<password>@<cluster-url>/test";
const client = new MongoClient(uri);

const { MongoClient } = require("mongodb");
const uri = "mongodb+srv://<username>:<password>@<cluster-url>/test";
const client = new MongoClient(uri);

Atlas supports integrations with AWS, Azure, and GCP, making deployments seamless.

Security Best Practices

Securing MongoDB is crucial for protecting sensitive data.

• Enable authentication and role-based access control.
• Use TLS/SSL for encrypted connections.
• Restrict access with firewall rules and IP whitelisting.
• Regularly apply MongoDB security patches.

MongoDB Atlas automates many of these protections by default.

Transactions in MongoDB

Since MongoDB 4.0, transactions are supported across multiple documents. They ensure ACID properties like relational databases.

Example:

const session = client.startSession();
session.startTransaction();
db.accounts.updateOne({ user: "Alice" }, { $inc: { balance: -100 } }, { session });
db.accounts.updateOne({ user: "Bob" }, { $inc: { balance: 100 } }, { session });
await session.commitTransaction();

const session = client.startSession();
session.startTransaction();
db.accounts.updateOne({ user: "Alice" }, { $inc: { balance: -100 } }, { session });
db.accounts.updateOne({ user: "Bob" }, { $inc: { balance: 100 } }, { session });
await session.commitTransaction();

Transactions are useful for financial applications where data consistency is critical.

MongoDB Shell vs. Compass

• MongoDB Shell (mongosh): Command-line tool for running queries.
• MongoDB Compass: GUI that helps visualize collections, indexes, and query results.

Both tools are widely used, with Compass being beginner-friendly and the shell favored by developers comfortable with scripts.

Backup and Restore

Backup ensures disaster recovery and data safety. MongoDB provides tools like mongodump and mongorestore.

Example backup:

mongodump --db=mydb --out=/backup/mydb

mongodump --db=mydb --out=/backup/mydb

Example restore:

mongorestore /backup/mydb

mongorestore /backup/mydb

Atlas users benefit from automated snapshots and point-in-time recovery.

Sharding in MongoDB

Sharding distributes data across multiple servers, allowing horizontal scaling. It is useful for massive datasets where a single machine can’t handle the load.

Example sharding setup:

sh.enableSharding("mydb")
sh.shardCollection("mydb.users", { userId: 1 })

sh.enableSharding("mydb")
sh.shardCollection("mydb.users", { userId: 1 })

Sharding ensures performance remains consistent as data grows.

Replication

Replication provides high availability by maintaining multiple copies of data across nodes.

Replica set benefits:

• Automatic failover
• Data redundancy
• Read scalability

A replica set typically includes a primary node and multiple secondary nodes.

Conclusion

This MongoDB Cheatsheet is a practical guide to MongoDB basics, CRUD operations, queries, aggregation, indexing, modeling, security, and Atlas. Keep it handy for fast lookups while working on MongoDB projects. For deeper knowledge, always refer to the official MongoDB documentation.

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