What are the differences between hash tables and binary search trees?

What are the differences between hash tables and binary search trees?

Hash tables and binary search trees (BST) are both data structures used for storing and retrieving data, but they have different characteristics. Hash tables use a hash function to compute an index into an array of buckets or slots, while BSTs maintain a sorted order of elements, allowing for efficient in-order traversal.

Which one is faster for searching?

In general, hash tables provide average-case O(1) time complexity for search operations, making them faster than binary search trees, which have O(log n) time complexity for balanced trees. However, the performance of hash tables can degrade to O(n) in the worst case due to collisions.

Are there any situations where a binary search tree is preferred?

Yes, binary search trees are preferred when you need to maintain a sorted order of elements, perform range queries, or when you want to avoid the potential for collisions that can occur in hash tables.

Can you explain how collisions are handled in hash tables?

Collisions in hash tables can be handled using various methods, such as chaining, where each slot in the hash table points to a linked list of entries that hash to the same index, or open addressing, where the algorithm searches for the next available slot.