YouTube video: https://youtu.be/_1IKwnbscQU?si=lkIYfbe3VgMrmYnA

Scaling a database is crucial as your application grows, handling increasing data volumes and user traffic. Without proper scaling, performance degrades, causing slow responses, timeouts, and crashes that harm user experience. This guide explains seven proven strategies to scale your database effectively, illustrated with practical examples.

Why and When to Scale Your Database

• Growth Trigger: As your user base and data volume increase, database load intensifies.
• Performance Risks: Without scaling, your app may become slow, unstable, or crash.
• Examples:
  • A startup goes viral, growing from thousands to millions of requests.
  • E-commerce platforms experiencing holiday sale surges need scalable databases for smooth peak load handling.

Key Takeaway: Scaling ensures smooth operations and preserves a good user experience during growth spikes.

1. Indexing

What is Indexing?

• Indexes function like a book’s index.
• They allow quick location of data without scanning entire tables.
• Common type: B-tree index.

How It Works

• B-tree indexes maintain sorted data.
• Ideal for quick insertion, deletion, lookup.
• Excellent for range queries (e.g., all orders within a date range; customers alphabetically).

Example