MongoDB Cheatsheet — Complete MongoDB Commands, Queries & Aggregation Guide

Table of Contents:

MongoDB Cheatsheet — Quick Reference for NoSQL Developers

MongoDB is a NoSQL document-based database designed for high scalability, flexibility, and performance. Instead of storing data in tables like SQL, MongoDB uses JSON-like documents known as BSON (Binary JSON).

This MongoDB Cheatsheet provides essential syntax, commands, and examples to help you query and manage databases effectively.

Basic MongoDB Concepts

Term	Description
Database	A container for collections.
Collection	Similar to a table in SQL.
Document	JSON-like data structure.
Field	Key-value pair inside a document.
BSON	Binary JSON format used for data storage.

Example Document:

{
  "_id": 1,
  "name": "John Doe",
  "age": 30,
  "skills": ["Python", "MongoDB", "Node.js"]
}

MongoDB Shell Basics

Command	Description
`show dbs`	List all databases
`use myDatabase`	Switch or create a database
`show collections`	List collections in the current database
`db.dropDatabase()`	Delete current database

CRUD Operations in MongoDB

CRUD = Create, Read, Update, Delete — the four basic operations in MongoDB.

Insert Documents

Insert a single document:

db.users.insertOne({ name: "Alice", age: 28, city: "New York" });

Insert multiple documents:

db.users.insertMany([
  { name: "Bob", age: 32 },
  { name: "Charlie", age: 25 }
]);

Read Documents

Retrieve all documents:

db.users.find();

Find documents with condition:

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

Pretty print results:

db.users.find().pretty();

Update Documents

Update one document:

db.users.updateOne(
  { name: "Alice" },
  { $set: { age: 29 } }
);

Update multiple documents:

db.users.updateMany(
  { city: "New York" },
  { $set: { city: "Los Angeles" } }
);

Delete Documents

Delete one:

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

Delete many:

db.users.deleteMany({ age: { $lt: 25 } });

MongoDB Query Operators

Operator	Description	Example
`$eq`	Equals	`{ age: { $eq: 25 } }`
`$ne`	Not equal	`{ city: { $ne: "London" } }`
`$gt` / `$lt`	Greater/Less than	`{ age: { $gt: 20 } }`
`$in` / `$nin`	In/Not in list	`{ city: { $in: ["Delhi", "Paris"] } }`
`$and`	Logical AND	`{ $and: [{ age: { $gt: 20 } }, { city: "Paris" }] }`
`$or`	Logical OR	`{ $or: [{ city: "London" }, { city: "Berlin" }] }`
`$exists`	Check if field exists	`{ phone: { $exists: true } }`

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MongoDB Projection

Select specific fields to return in the query result.

db.users.find({}, { name: 1, city: 1, _id: 0 });

MongoDB Sorting and Limiting

db.users.find().sort({ age: 1 }); // Ascending
db.users.find().sort({ age: -1 }); // Descending
db.users.find().limit(5); // First 5 documents

Aggregation Pipeline

Aggregation allows data transformation and computation like SQL GROUP BY.

Basic example:

db.users.aggregate([
  { $match: { age: { $gte: 25 } } },
  { $group: { _id: "$city", total: { $sum: 1 } } }
]);

Common Aggregation Operators:

Operator	Usage	Example
`$match`	Filter documents	`{ $match: { city: "London" } }`
`$group`	Group by field	`{ $group: { _id: "$city", total: { $sum: 1 } } }`
`$sort`	Sort results	`{ $sort: { total: -1 } }`
`$project`	Select specific fields	`{ $project: { name: 1, city: 1 } }`
`$limit`	Limit number of results	`{ $limit: 10 }`

MongoDB Indexing

Indexes speed up data retrieval operations.

Create an index:

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

View indexes:

db.users.getIndexes();

Drop an index:

db.users.dropIndex("name_1");

MongoDB Relationships (Embedding vs Referencing)

Type	Description	Example
Embedding	Store related data in the same document.	`{ name: "Alice", address: { city: "NY", zip: 10001 } }`
Referencing	Store reference (ID) to another collection.	`{ user_id: ObjectId("..."), order_id: ObjectId("...") }`

Tip: Use embedding for one-to-few and referencing for one-to-many relationships.

MongoDB Backup and Restore

Backup a database:

mongodump --db myDatabase --out /backup/

Restore a database:

mongorestore /backup/myDatabase

FAQ — MongoDB Cheatsheet

Q1: What is MongoDB used for?
MongoDB is used for storing unstructured or semi-structured data in JSON format for web apps, analytics, and IoT platforms.

Q2: Is MongoDB faster than SQL?
For large, unstructured data and high read/write operations, MongoDB can outperform traditional SQL databases.

Q3: How is data stored in MongoDB?
MongoDB stores data as BSON documents inside collections.

Q4: What language is MongoDB written in?
MongoDB is written in C++, JavaScript, and Go.

Q5: What is the default port for MongoDB?
The default port number is 27017.