In competitive programming, you rarely implement balanced BSTs from scratch. Instead: Use language libraries: - C++: set, map, multiset (Red-Black trees) - Java: TreeSet, TreeMap - Python: sortedcontainers (not built-in, but available) When you need: - Ordered iteration: BST gives sorted order naturally - Range queries: find all elements in - Predecessor/successor: find closest smaller/larger value - Rank queries: augment with subtree sizes When hash tables are better: - Only need insert/delete/lookup (no ordering) - Keys aren't naturally comparable When arrays + sorting is better: - Static data (no insertions after initial load) - Binary search on sorted array is simpler
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$ curl repovive.com/roadmaps/data-structures/binary-search-trees/when-to-use-bsts
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