Operating systems represent file/directory structures as N-ary trees:

/home/
├── user/
│   ├── documents/
│   │   ├── resume.pdf
│   │   └── notes.txt
│   └── downloads/
└── shared/

• Each directory is a node; files are leaves.
• DFS is used for du (disk usage), find command, antivirus scans.
• BFS is used for file search at shallowest level first.

Databases use B-Trees and B+ Trees (generalized balanced BSTs) for indexing:

• B+ Trees power indexes in MySQL, PostgreSQL, SQLite.
• Nodes contain multiple keys (to fit disk pages of ~4KB).
• All data is in leaf nodes; internal nodes are just keys for routing.
• Guarantees O(log N) search, insert, delete even for billions of records.
• Sequential scans are fast because leaf nodes are linked.

Search engines, IDEs, and keyboard apps use Tries:

• Typing “app” traverses root → ‘a’ → ‘p’ → ‘p’
• All words under that node are candidates: “apple”, “application”, “apply”
• Advantages over HashMap: Common prefix sharing saves memory; range queries are natural.
• Extension: Compressed Trie (Patricia Trie / Radix Tree) merges single-child chains.

When asked “Why use a tree?” in interviews:

• Special Trees — Trie, Heap, Segment Tree
• Tree Traversals — DFS & BFS
• Interview Questions — Practice problems