Glossary
B-Tree
A balanced tree data structure optimized for storage systems that read and write blocks of sorted data.
After this, you will understand
How B-Tree helps you see what the term means, where it appears, and why engineers care about it in real systems.
Treat the idea as a definition to memorize.
Real systems force the idea to handle Indexing, Disk Locality, and Range Queries.
Use the concept to decide what the system guarantees, what it risks, and what it costs to operate.
Think before readingWhere would B-Tree appear in a real production system, and what failure or bottleneck would it help you reason about?
Reading in progress
This page is saved in your local study history so you can continue later.
Concepts Covered
- B-tree indexes
- Balanced search trees
- Disk locality
- Range scans
- Page splits
- Database lookup performance
Definition
A B-tree is a balanced search tree that stores many keys per node. Database storage engines use B-tree variants because they minimize random I/O and preserve sorted order for efficient range scans.
Why systems engineers care
Indexes are not abstract magic. Their shape influences write amplification, read latency, lock behavior, cache locality, and query planning. Understanding B-trees helps explain why some predicates are cheap and others are expensive.
Useful intuition
Compared with a binary tree, a B-tree is wide and shallow. Each node can hold many keys, so a lookup usually touches only a small number of pages.
| Operation | Typical property |
|---|---|
| Point lookup | Traverses root to leaf |
| Range scan | Walks sorted leaves |
| Insert | May split pages |
| Delete | May rebalance or leave space |
What to study next
These links keep the session moving: read prerequisites first, then open the systems, concepts, and patterns that deepen this page.
Related Concepts
Core ideas that connect to this topic.