Computer science · Curated list
Hash table, Linked list, Binary search tree and 22 more, ranked by how much of the world has written about each one.
Most written-about first. Each description summarises the data structure's Wikipedia article, which its name links to.
1
Associative array for storing key–value pairs
A data structure of computer science implementing an associative array, which is also known as a map or a dictionary: an abstract data type mapping keys to values. A hash function turns each key into an index, or hash code, pointing into an array of slots or buckets, where the value sought can be found.
2
Data structure with nodes pointing to the next node
A linear collection of data elements in computer science whose order does not come from where they sit in memory; instead, every element holds a pointer to the one after it.
3
Rooted binary tree data structure
Also called an ordered or sorted binary tree, a rooted binary tree data structure in which each internal node's key is greater than every key in its left subtree and less than every key in its right subtree. Operations on it take time linear in the height of the tree.
Wikidata · Photo: No machine-readable author provided. Dcoetzee assumed (based on copyright claims)., Public domain
4
Self-balancing binary search tree data structure
A self-balancing binary search tree of computer science, known for storing and retrieving ordered information quickly. Each node carries an extra "color" bit, often drawn as red or black, which helps keep the tree roughly balanced at all times.
Wikidata · Photo: Nomen4Omen, CC BY-SA 4.0
5
Tree-based computer data structure
A self-balancing tree data structure of computer science that keeps data sorted and supports searching, sequential access, insertion and deletion in logarithmic time. It generalises the binary search tree by letting nodes have more than two children.
6
7
Type of data structure
Also called a hash tree, a tree used in computer science and cryptography in which every "leaf" node carries the cryptographic hash of a block of data, and every other node carries the cryptographic hash of its children's labels. It allows the contents of a large data structure to be checked efficiently and securely.
Variant of heap data structure
A heap data structure shaped as a binary tree, and a common way to implement priority queues.
10
Data structure for approximate set membership
A probabilistic data structure, economical with space, that Burton Howard Bloom conceived in 1970 for testing whether an element belongs to a set. It can give false positives but never false negatives: a query answers either "possibly in set" or "definitely not in set".
Data structure for storing non-overlapping sets
A data structure of computer science, also known as a merge–find set or union–find data structure, that holds a collection of disjoint (non-overlapping) sets; put another way, it stores the partition of a set into disjoint subsets.
12
Set of polygons to define the surface of a 3D model
In solid modelling and 3D computer graphics, a collection of vertices, edges and faces defining the shape of the surface of a polyhedral object. It makes rendering simpler, as in a wire-frame model.
Wikidata · Photo: en:User:Chrschn, Public domain
Self-adjusting binary search tree
A binary search tree with the extra property that elements used recently are quick to reach again. Like self-balancing binary search trees, it performs its basic operations, among them removal, look-up and insertion, in O(log n) amortised time.
Data structure representing a graph
In computer science and graph theory, a way of representing a finite graph as a set of unordered lists, one per vertex, each holding that vertex's neighbours.
Data structure that acts as a priority queue
A data structure of computer science that works as a priority queue. It is a mergeable heap: two heaps can be merged in logarithmic time.
Data structures used in spatial indexing
Tree data structures for spatial access methods, meaning the indexing of information in several dimensions, such as polygons, rectangles or geographical coordinates. Antonin Guttman proposed the R-tree in 1984, and it has seen considerable use in both applied and theoretical work.
Data structure for priority queue operations
A data structure of computer science for priority queue operations, made of a collection of heap-ordered trees. Its amortised running time is better than that of many other priority queue structures, the binomial heap and binary heap among them.
23
Tree data structure that partitions a 2D area
A tree data structure in which every internal node has exactly four children. The two-dimensional counterpart of octrees, quadtrees are most often used to partition a flat space by splitting it again and again into four regions, or quadrants.
Wikidata · Photo: David Eppstein, Public domain
24
List data structure to which elements can be added/removed
Also called a growable, resizable or mutable array, a dynamic table or an array list, a list data structure of computer science with random access and variable size, to which elements can be added and from which they can be removed. Many modern mainstream programming languages provide one in their standard libraries.
Data structure in computer science
A self-balancing data structure of computer science that can serve to implement dictionaries.
Every Wikidata item that is a data structure, or a kind of one — leaving out cryptocurrencies and file formats, which Wikidata also files there, and that has its own English Wikipedia article, ranked by the number of Wikimedia sites with a page about it — Wikipedia's language editions, mostly, and sister projects such as Wikiquote. That counts how many communities independently thought it worth describing, and nobody can buy a place on it. The top 25 are shown.
Wikidata files these under this list's query, but they are not what the list is about:
Fetched from Wikidata on 2026-09-25. Each description is this site's summary of the entry's Wikipedia article, which its name links to: the wording is ours, the facts are Wikipedia's, licensed CC BY-SA 4.0. To correct an entry, correct it there; the next refresh carries the change.
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