Data structure

A data structure organizes and stores data so operations such as access, insertion, deletion, and search can be performed efficiently.

Array: A sequence of elements stored in indexed positions, typically with constant-time access by index. Arrays provide direct indexed access but make insertion within the sequence costly.
Abstract data type: A specification of a data type defined by its values and operations, independent of implementation. It separates the behavior a structure promises from how it stores data.
Database index: An auxiliary structure that accelerates retrieval of records from a database table. Database indexes organize keys to avoid scanning every stored record.
Static array: An array whose capacity is fixed when it is created. Its fixed capacity contrasts with structures that grow as elements are added.
Linked list: A sequence of nodes in which each node links to the next, or to both neighbors. Linked lists trade direct indexing for efficient insertion or removal when a node is known.
Time complexity: A measure of how an algorithm's running time grows with input size. Operation costs determine whether a structure remains efficient as data grows.
B-tree: A balanced search tree whose nodes hold multiple keys and children, designed for block storage. B-trees reduce disk accesses in database and filesystem indexes.
Dynamic array: An array-like structure that resizes its allocated storage as elements are added or removed. It preserves indexed access while avoiding the fixed capacity of a static array.
Hash table: A structure that maps keys to values using a hash function to select storage locations. Hash tables organize key-value data for fast average-case lookup and updates.
Space complexity: A measure of how an algorithm's memory use grows with input size. Memory overhead can make a fast structure impractical under limited storage.

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