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.
