Final answer:
Hash tables are distinguished by constant time complexity for insertion, deletion, and access operations. This is unlike other data structures which may have linear or logarithmic time complexities. In most practical situations, hash tables achieve near-instant operations due to efficient hashing.
Step-by-step explanation:
What differentiates hash tables from other data structures in terms of runtime is their ability to have constant time complexity for insertion, deletion, and access operations under ideal circumstances. Unlike other data structures such as arrays (which can have linear time complexity for insertion and deletion) or binary search trees (which have logarithmic time complexity for various operations), hash tables are designed to perform these operations very quickly.
When a key is added to a hash table, a hash function is used to compute an index at which the value should be stored. If the hash function is good and the hash table is properly sized with minimal collisions, the average time complexity for each of these operations is O(1), or constant time. However, in the worst-case scenario, such as when too many elements have collided at the same index leading to long linked lists or chains, the operations can degrade to O(n), or linear time complexity. Nevertheless, hash tables are typically associated with constant time complexity due to their efficiency in most practical situations.