B-Tree
Domain: Data Structures
🎯 Motivation
When data is too large for memory and lives on disk — databases, file systems — B-trees minimise disk reads by storing many keys per node.
📋 Concrete Example
A B-tree node might hold 100 keys and 101 child pointers. This means fewer levels, fewer disk reads. Database indexes use B-trees extensively.
🔗 Analogy
A library where each shelf holds 100 books (not just 1). You find the right shelf in 2-3 steps instead of 10, saving time walking through the stacks.