Documents and Collections

The two fundamental building blocks of MongoDB are documents and collections. Understanding these concepts deeply will help you design efficient data models from the start.

Documents

A MongoDB document is a set of field-value pairs stored in BSON format. Every document must have a top-level _id field that uniquely identifies it within its collection. If you do not supply _id when inserting, MongoDB automatically generates an ObjectId.

{
  _id: ObjectId("64b2e3f1a2b3c4d5e6f70001"),
  title: "Getting Started with MongoDB",
  author: "Jane Smith",
  tags: ["mongodb", "nosql", "database"],
  publishedAt: new Date("2024-03-15"),
  stats: {
    views: 4200,
    likes: 318
  }
}

Documents can contain nested documents (embedded documents) and arrays, allowing you to represent rich, hierarchical data in a single record. This is one of the most powerful aspects of the document model.

Supported BSON Types

MongoDB supports all standard JSON types — String, Number, Boolean, Array, Object, and Null — plus BSON-specific types:

• ObjectId — a 12-byte unique identifier (the default _id type)
• Date — milliseconds since the Unix epoch
• Decimal128 — high-precision decimal for financial data
• Binary — arbitrary binary data (images, files)
• Regular Expression — stored patterns for server-side regex queries

Collections

A collection is a group of documents, analogous to a table in a relational database. Collections do not enforce a schema by default, meaning documents within the same collection can have different fields.

// Both documents can coexist in the same "products" collection
{ _id: 1, name: "T-Shirt", size: "M", colour: "blue" }
{ _id: 2, name: "Laptop", ram: "16GB", storage: "512GB SSD" }

Collections are created implicitly the first time you insert a document into them. There is no CREATE TABLE equivalent needed.

Databases

Above collections sits the database level. A single MongoDB server (or cluster) can host many databases, each containing its own set of collections. Databases are also created implicitly.

use myapp          // switch to (or create) the myapp database
db.users.find()    // access the users collection

Schema Validation

Although MongoDB is schema-flexible, you can enforce structure using JSON Schema validation rules applied to a collection. This gives you the best of both worlds: flexibility where needed, constraints where critical.

db.createCollection("orders", {
  validator: {
    $jsonSchema: {
      bsonType: "object",
      required: ["customerId", "total"],
      properties: {
        total: { bsonType: "decimal" }
      }
    }
  }
})