What is DATABASE SHARDING | REPLICATION VS SHARDING (Day 08)

Learn Replication and Database Sharding in system design with real-world examples, scaling strategies, and high-availability techniques used by companies like Facebook, Netflix, Amazon, and Instagram.

In this video, we explain what replication is, how it ensures fault tolerance, disaster recovery, and zero-downtime systems, and why modern distributed databases maintain multiple synchronized copies of data.

Then we break down database sharding, how data is split across shards for horizontal scaling, how sharding improves performance under massive traffic, and when to use sharding vs replication in backend architecture.

You’ll also learn sharding strategies (range-based, hash-based, directory-based), common challenges like re-sharding & hotspotting, and best practices to design scalable, distributed databases without data inconsistency.

This tutorial is perfect for system design interviews, backend developers, DevOps engineers, cloud architects, and anyone who wants to master distributed database systems.

⏱️ Timestamps

00:00 – Syllabus Overview
00:32 – What is Replication?
03:50 – Brief Overview of Sharding
05:26 – What is Database Sharding?
08:00 – Benefits of Sharding
11:16 – How Sharding Works?
13:00 – Sharding Strategies (Range, Hash, Directory, Geo)
17:50 – Challenges with Sharding
19:18 – Best Sharding Practices
21:00 – Summary

✅ What You Will Learn

Replication vs Sharding in distributed systems

How replication improves high availability & read performance

How sharding enables horizontal scaling

Difference between vertical vs horizontal scaling

Real-world use cases in SQL & NoSQL databases

Sharding strategies and anti-patterns

Handling rebalancing, failures, and hotspots

Best practices for system design interviews

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