Binary Search Tree vs Hash Table: Which is Better?

What are the main differences between a binary search tree and a hash table?

A binary search tree (BST) is a data structure that maintains sorted data and allows for efficient searching, insertion, and deletion. A hash table, on the other hand, uses a hash function to map keys to values, providing average-case constant time complexity for lookups.

When should I use a binary search tree instead of a hash table?

You should use a BST when you need to maintain sorted order and perform range queries. Hash tables are better for quick lookups when order is not important.

What are the time complexities for searching in both data structures?

For a balanced binary search tree, the average and worst-case time complexity for searching is O(log n). For a hash table, the average-case time complexity is O(1), but it can degrade to O(n) in the worst case due to collisions.

Can you give me an example of when a hash table might be more efficient?

Sure! If you're implementing a caching system where you need to quickly retrieve values based on unique keys, a hash table would be more efficient due to its average O(1) lookup time.