SQL vs NoSQL

# SQL vs NoSQL

| Feature | SQL | NoSQL |
|------------------|--------------------------|---------------------------|
| Schema | Fixed schema | Dynamic/flexible schema |
| Data Model | Tables (rows, columns) | Documents, Key-Value, |
| | | Column-family, Graph |
| Scaling | Vertical (scale up) | Horizontal (scale out) |
| ACID | Full support | Varies (eventual consistency) |
| Joins | Complex joins easy | Joins expensive/nahi hote |
| Query Language | SQL (standardized) | Database-specific APIs |
| Use Case | Transactions, reporting | Real-time, big data |
| Examples | MySQL, PostgreSQL | MongoDB, Redis, Cassandra |

# Key Decision Factors:
1. Data structure fixed hai — SQL
2. Data structure change hota rahega — NoSQL
3. ACID transactions chahiye — SQL
4. Massive scale chahiye — NoSQL
5. Complex queries/JOINs — SQL
6. Simple key-value access — NoSQL

# SQL Database: MySQL / PostgreSQL

# Example Schema:
CREATE TABLE users (
 id INT PRIMARY KEY,
 name VARCHAR(100),
 email VARCHAR(100) UNIQUE
);

CREATE TABLE orders (
 id INT PRIMARY KEY,
 user_id INT,
 amount DECIMAL,
 FOREIGN KEY (user_id) REFERENCES users(id)
);

# Query: User ke saare orders
SELECT u.name, o.amount 
FROM users u 
JOIN orders o ON u.id = o.user_id
WHERE u.id = 1;

# Pros:
? ACID compliant (Atomicity, Consistency, Isolation, Durability)
? Complex queries with JOINs
? Data integrity enforced
? Standard SQL — portable across databases

# Cons:
? Vertical scaling limit
? Schema changes mushkil (ALTER TABLE)
? Not great for unstructured data

# 1. Document Database (MongoDB)
? JSON-like documents store karte hain
? Flexible schema — har document alag ho sakta hai

{
 "_id": 123,
 "name": "Vaibhav",
 "email": "vaibhav@example.com",
 "orders": [
 {"item": "laptop", "amount": 50000},
 {"item": "phone", "amount": 25000}
 ]
}

# 2. Key-Value (Redis, DynamoDB)
? Sabse simple — key se value lo
? Blazing fast — O(1) access

SET user:123 '{"name": "Vaibhav"}'
GET user:123

# 3. Column-Family (Cassandra, HBase)
? Large-scale data, write-heavy
? Horizontal scaling bahut achi

# 4. Graph Database (Neo4j)
? Relationships important hain
? Social networks, recommendations

# Netflix:
? User data: Cassandra (NoSQL) — massive scale
? Billing: PostgreSQL (SQL) — ACID transactions
? Recommendations: Neo4j (Graph) — user connections
? Caching: Redis (Key-Value) — fast access

# Uber:
? Ride data: MySQL (SQL) — transactions
? Real-time tracking: Redis (Key-Value) — low latency
? Analytics: Cassandra (NoSQL) — write-heavy

# Instagram:
? User data: PostgreSQL (SQL) — relationships
? Feed: Redis (Key-Value) — caching
? Media metadata: Cassandra (NoSQL) — scale

# Lesson: Most systems use POLYGLOT PERSISTENCE
# Different data — Different database