Document Store

📄 What is a Document Store?

A Document Store (or Document-Oriented Database) is a type of NoSQL database that stores data as documents, typically in JSON, BSON, or XML format.

Each document is a self-contained, semi-structured unit that can have its own unique structure — no fixed schema required.

🧱 Core Concepts

Term	Description
Document	A self-contained data unit, usually JSON. Contains key-value pairs, arrays, and nested objects.
Collection	A group of related documents (like a table in SQL).
Key (_id)	A unique identifier for each document.
Schema-less	Documents in the same collection can have different fields or structures.

📄 Example Document (JSON)

{
  "_id": "user123",
  "name": "Alice",
  "age": 28,
  "interests": ["travel", "coding"],
  "address": {
    "city": "Mumbai",
    "pin": 400001
  }
}

This document could live in a users collection, and another document might have an entirely different structure.

🧠 Why Use a Document Store?

Feature	Advantage
Schema flexibility	Easy to evolve structure without migrations.
Nested data support	Can store arrays and objects naturally.
Horizontal scalability	Built for cloud-native and large-scale applications.
JSON-friendly	Aligns well with REST APIs, frontends, and microservices.

⚙️ Popular Document Databases

Database	Highlights
MongoDB	Most popular, uses BSON format, rich querying & indexing.
CouchDB	Sync-friendly, uses JSON + HTTP APIs.
Firebase Firestore	Real-time sync and built-in offline support.
Amazon DocumentDB	MongoDB-compatible managed service by AWS.

🧪 Querying Example (MongoDB)

db.users.find({ "address.city": "Mumbai" });

Fetch all users who live in Mumbai.

✅ Pros

Easy to work with — structure mimics JSON objects used in modern apps.
Flexible schema makes it developer-friendly.
Scales horizontally and supports sharding.
Great performance on read-heavy and write-heavy workloads.

❌ Cons

No native joins (can be mimicked but expensive).
Data redundancy can occur (denormalization is common).
Not ideal for complex transactions or strict ACID use cases.

📌 Use Cases

Content management systems (CMS)
Product catalogs
User profiles and activity logs
Mobile and web apps (especially with real-time features)
E-commerce platforms

🔄 Comparison with RDBMS

Feature	RDBMS	Document Store
Schema	Rigid	Flexible (dynamic per document)
Data Format	Rows & Columns	JSON-like Documents
Joins	Yes	No (denormalize instead)
Ideal for	Structured, relational data	Semi-structured, nested data

If you’re building something like a blog, e-commerce platform, or dashboard, a document store like MongoDB can be a killer choice.

Gaurav’s Notes

Explorer