Essential data structures include arrays, linked lists, stacks, queues, hash maps, trees, graphs, and heaps, each serving different problem needs.

Competitive programming relies heavily on various data structures, each of which is suited to specific types of problems. Arrays and linked lists provide basic data storage, while stacks and queues are useful for ordered data processing. Hash maps allow for quick access to data, crucial for lookup-heavy problems. Trees, such as binary search trees and segment trees, are vital for range-based queries and hierarchical data. Graphs represent networks and relationships, essential for pathfinding and connectivity problems. Heaps facilitate efficient priority-based data retrieval, helpful in problems requiring quick access to minimum or maximum values. By mastering these data structures and understanding their strengths and limitations, competitive programmers can tackle a diverse set of problems with speed and accuracy.