Key–value database

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. Dictionaries contain a collection of objects, or records, which in turn have many different fields within them, each containing data. These records are stored and retrieved using a key that uniquely identifies the record, and is used to find the data within the database.

A table showing different formatted data values associated with different keys

Key–value databases work in a very different fashion from the better known relational databases (RDB). RDBs predefine the data structure in the database as a series of tables containing fields with well defined data types. Exposing the data types to the database program allows it to apply a number of optimizations. In contrast, key–value systems treat the data as a single opaque collection, which may have different fields for every record. This offers considerable flexibility and more closely follows modern concepts like object-oriented programming. Because optional values are not represented by placeholders or input parameters, as in most RDBs, key–value databases often use far less memory to store the same database, which can lead to large performance gains in certain workloads.^{[citation needed]}

Performance, a lack of standardization and other issues limited key–value systems to niche uses for many years, but the rapid move to cloud computing after 2010 has led to a renaissance as part of the broader NoSQL movement. Some graph databases, such as ArangoDB,^[1] are also key–value databases internally, adding the concept of the relationships (pointers) between records as a first class data type.