🚀 Coding Interview Questions with Answers — Part 8

📂 Databases & Backend Theory

🚀 71. What is the difference between SQL and NoSQL?

🔹 SQL Databases
SQL databases are:
• Relational Databases
They store data in:
• Tables
• Rows
• Columns

Examples:
• MySQL
• PostgreSQL

🔹 Features
✅ Structured schema
✅ ACID compliance
✅ Strong consistency

🔹 NoSQL Databases
NoSQL databases are:
• Non-relational Databases

Examples:
• MongoDB
• Cassandra

🔹 Features
✅ Flexible schema
✅ Horizontal scalability
✅ High availability

🔹 Comparison

SQL
• Structured
• Tables
• Vertical scaling
• Complex joins

NoSQL
• Flexible
• Documents/Key-Value
• Horizontal scaling
• Fast distributed access

🔹 Interview Tip
Use:
SQL → structured transactional systems
NoSQL → large-scale distributed systems

🚀 72. What is ACID and where is it important?
ACID properties ensure reliable database transactions.

🔹 ACID Meaning

A
• Meaning: Atomicity

C
• Meaning: Consistency

I
• Meaning: Isolation

D
• Meaning: Durability

🔹 Atomicity
All or nothing
If one step fails: Entire transaction rolls back

🔹 Consistency
Database remains valid after transaction.

🔹 Isolation
Concurrent transactions should not interfere.

🔹 Durability
Committed data survives crashes.

🔹 Important In
✅ Banking systems
✅ Payment systems
✅ Order processing

🔹 Interview Tip
ACID is heavily asked in backend interviews.

🚀 73. What is normalization and denormalization?

🔹 Normalization
Organizing data to:
• Reduce redundancy
• Improve consistency

🔹 Example
Instead of repeating user info: Store user once and reference with IDs.

🔹 Benefits
✅ Reduces duplication
✅ Better integrity
✅ Easier updates

🔹 Denormalization
Adding redundancy intentionally for: Faster reads

🔹 Benefits
✅ Faster queries
✅ Better performance

🔹 Drawbacks
❌ Data duplication
❌ Update complexity

🔹 Interview Tip
Normalized → OLTP systems
Denormalized → analytics/read-heavy systems

🚀 74. What is indexing and when is it useful?
Indexes improve query speed.

🔹 Without Index
Database scans: Entire table

🔹 With Index
Database directly jumps to rows.
Similar to: Book index

🔹 SQL Example
CREATE INDEX idx_name
ON users(name);

🔹 Benefits
✅ Faster SELECT queries
✅ Faster filtering
✅ Faster joins

🔹 Drawbacks
❌ Extra storage
❌ Slower inserts/updates

🔹 Interview Tip
Indexes optimize reads but impact writes.

🚀 75. What is sharding vs replication?

🔹 Replication
Copy same database across multiple servers.

🔹 Goal
✅ High availability
✅ Backup
✅ Read scaling

🔹 Example
Primary → Replica Servers

🔹 Sharding
Split database into parts.
Each shard stores: Different subset of data

🔹 Example

Shard 1
• Data: Users A-M

Shard 2
• Data: Users N-Z

🔹 Comparison

Replication
• Copies same data
• Improves availability

Sharding
• Splits data
• Improves scalability

🔹 Interview Tip
Large-scale systems often use both.

🚀 76. What is the difference between strong and eventual consistency?

🔹 Strong Consistency
Every read gets: Latest data immediately

🔹 Example
Banking systems.

🔹 Eventual Consistency
Updates propagate gradually.
Eventually: All nodes become consistent

🔹 Example
Social media likes/views.

🔹 Comparison

Strong
• Immediate accuracy
• Slower

Eventual
• Temporary inconsistency
• Faster/scalable

🔹 Interview Tip
Distributed systems often trade consistency for scalability.

🚀 77. What is a transaction and when do you roll it back?
Transaction: Group of operations executed together

🔹 Example
Bank transfer:
1. Debit sender
2. Credit receiver

Both must succeed.

🔹 Rollback Happens When
✅ Error occurs
✅ Constraint fails
✅ System crash
✅ Validation failure