Design Thread-Safe Trie
Last Updated: February 1, 2026
A trie excels at prefix operations, making it ideal for autocomplete, spell-checking, IP routing tables, and DNS lookups. But tries have a unique concurrency problem: multiple words share the same prefix nodes. When two threads insert "apple" and "application" simultaneously, they both traverse and potentially modify the shared path "a" → "p" → "p" → "l". One wrong interleaving, and you lose words or corrupt the structure.
This chapter explores three approaches to building thread-safe tries, from simple global locking to sophisticated copy-on-write techniques optimized for read-heavy workloads.
Problem Statement
What We're Building
A thread-safe trie (prefix tree) that allows multiple threads to insert, search, and delete words concurrently without data corruption or lost updates. The structure must support efficient prefix queries, the core operation that makes tries valuable.
Required Operations
| Operation | Description | Expected Complexity |
|---|---|---|
insert(word) | Add a word to the trie | O(m) where m = word length |
search(word) | Check if exact word exists | O(m) |
startsWith(prefix) | Check if any word has given prefix | O(m) |
delete(word) | Remove a word from the trie | O(m) |
getWordsWithPrefix(prefix) | Return all words with given prefix | O(m + k) where k = results |
Thread-Safety Requirements
- Multiple threads can search simultaneously without blocking each other
- Multiple threads can insert different words simultaneously
- A word is never lost during concurrent insertions
- A search never returns a partially inserted word
- Delete operations don't corrupt ongoing prefix traversals
- The structure never enters an invalid state regardless of thread interleaving