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A trie (pronounced "try" and short for *retrieval*) is a tree-like data structure used for efficient storage and retrieval of strings, particularly useful in applications involving autocomplete, spell-checking, and dictionary implementations. Introduced by Edward Fredkin in 1960, tries are optimized for prefix-based searches, where queries often involve partial matches rather than exact matches.

In a trie, each node represents a character, and paths from the root to nodes spell out prefixes or entire words. Child nodes branch out from a parent node based on subsequent characters, forming a directed acyclic graph (DAG) when shared prefixes are collapsed. For example, storing "cat," "car," and "caterpillar" would share the common prefix "ca," reducing memory usage.

Tries excel in scenarios requiring fast prefix searches, such as autocomplete systems, where suggestions are generated from partial inputs. However, they consume more memory than hash tables for large datasets due to their explicit structure. Variations like compressed tries (radix trees) or ternary search tries optimize space by merging nodes with single children.

Common operations include insertion, deletion, and search, all of which operate in time proportional to the length of the key being processed. Tries are widely used in programming languages, databases, and search engines for efficient string manipulation tasks.