Tries, also known as prefix trees or digital trees, are tree-based data structures that are primarily used for efficient retrieval and storage of strings. The name "trie" comes from the word "retrieval" or "retriever."

In a trie, each node represents a single character or a sequence of characters. The root node represents an empty string, and the children of each node represent the possible characters that can follow the current character. The edges of the trie represent the links between the nodes, indicating the transitions from one character to another.

The main advantage of tries is their ability to store and search for strings efficiently. Tries provide fast lookup and insertion operations, making them suitable for tasks such as autocomplete suggestions, spell checking, and dictionary implementations. Tries can also be used for tasks like pattern matching and string manipulation.


Tries, or prefix trees, can be categorized into different types based on their specific variations and optimizations. Here are three common types of tries:

Standard Tries: Also known as uncompressed tries, standard tries store each character of a string in a separate node. Each node represents a single character, and the edges represent the transitions from one character to another. While standard tries provide efficient string search and retrieval, they can be memory-intensive, especially for large dictionaries or datasets.

Compressed Tries: Compressed tries aim to reduce the memory requirements of standard tries by compressing common prefixes. Various compression techniques, such as path compression or node compression, are applied to merge nodes with single children or compress repeated characters. Compressed tries optimize the storage space, making them more efficient for large dictionaries or datasets with shared prefixes.

Suffix Tries: Suffix tries, also known as suffix trees, are a special type of trie that represents all the suffixes of a given string. They are commonly used for pattern matching, substring search, and various string-related algorithms. Suffix tries are constructed by adding each suffix of a string into the trie, enabling efficient search for any substring or pattern within the original string.

These different types of tries offer trade-offs between storage space, construction time, and query performance. The choice of trie type depends on the specific requirements and constraints of the application at hand.