What are the differences between a Binary Search Tree and a Hash Table?

What are the 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 for fast data retrieval.

Which one is more efficient for searching?

In general, a Hash Table offers average-case O(1) time complexity for search operations, while a BST has O(log n) time complexity if balanced. However, the efficiency can depend on the specific use case and data distribution.

Are there any scenarios where a BST is preferred over a Hash Table?

Yes, a BST is preferred when you need to maintain sorted order of elements, perform range queries, or when the data structure needs to support ordered operations.

What about memory usage? How do they compare?

Hash Tables can use more memory due to the need for extra space for the hash table itself and potential collisions. BSTs typically use less memory but can become inefficient if not balanced.