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A name–value pair, also called an attribute–value pair, key–value pair, or field–value pair, is a fundamental data representation in computing systems and applications. Designers often desire an open-ended data structure that allows for future extension without modifying existing code or data.
This subtle difference impacts in graphs with some kinds of cycles, where weak pairs do not describe correctly that an object ought to be "almost collectable". For example, consider a key-value pair with weak references where the key is an object and the value is a set of properties attached to the object.
In JavaScript, an "object" is a mutable collection of key-value pairs (called "properties"), where each key is either a string or a guaranteed-unique "symbol"; any other value, when used as a key, is first coerced to a string. Aside from the seven "primitive" data types, every value in JavaScript is an object. [50]
remove a (,) pair from the collection, unmapping a given key from its value. The argument to this operation is the key. Lookup, find, or get find the value (if any) that is bound to a given key. The argument to this operation is the key, and the value is returned from the operation.
A tabular data card proposed for Babbage's Analytical Engine showing a key–value pair, in this instance a number and its base-ten logarithm. A key–value database, or key–value store, is a data storage paradigm designed for storing, retrieving, and managing associative arrays, and a data structure more commonly known today as a dictionary or hash table.
In this model, data is represented as a collection of key–value pairs, such that each possible key appears at most once in the collection. [26] [27] The key–value model is one of the simplest non-trivial data models, and richer data models are often implemented as an extension of it.
Syntactic heterogeneity – differences in the language used for representing the elements Structural heterogeneity – differences in the types, structures of the elements Model / Representational heterogeneity – differences in the underlying models (database, ontologies) or their representations (key-value pairs, relational, document, XML ...
The difference [contradictory] lies in the way the data is processed; in a key-value store, the data is considered to be inherently opaque to the database, whereas a document-oriented system relies on internal structure in the document in order to extract metadata that the database engine uses for further optimization.