You know arrays, linked lists, and hash tables—they’re essential tools for coding. But what happens when they aren’t enough? Here are 5 weird but incredibly useful data structures you should know about.
1. B-Tree: Super-Sized, Organized Filing
B-Trees allow nodes to point to many children, keeping trees flatter and wider. This makes searching large datasets faster, and databases and file systems rely on them heavily.
2. Radix Tree: For Shared Prefixes
Radix Trees (Tries) compact shared prefixes, making them ideal for IP routing, autocompletion, and dictionary lookups.
3. Rope: Chopping Up Giant Texts
Ropes split large strings into smaller segments, making text edits in huge documents fast and efficient. Used in text editors like Google Docs.
4. Bloom Filter: The Probabilistic Bouncer
Bloom Filters quickly check if an item is definitely NOT in a set or maybe is. They’re memory-efficient and great for username checks, web crawlers, and large datasets.
5. Cuckoo Hashing: Eviction for Fast Lookups
Cuckoo Hashing handles collisions by having multiple possible locations per item. If a spot is taken, the new item evicts the old one, ensuring constant-time lookups—perfect for routers and performance-critical systems.
These unusual structures solve complex problems in clever ways. Knowing them expands your toolkit as a developer. What other weird but useful data structures have you used? Share in the comments!
“You know arrays, linked lists, and hash tables—they’re essential tools for coding. But what happens when they aren’t enough? Here are 5 weird but incredibly useful data structures you should know abou...”
Aman Kumar
Developer