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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.
Example of a web form with name-value pairs. 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.
The data structures used by NoSQL databases (e.g. key–value pair, wide column, graph, or document) are different from those used by default in relational databases, making some operations faster in NoSQL. The particular suitability of a given NoSQL database depends on the problem it must solve.
Berkeley DB (BDB) is an embedded database software library for key/value data, historically significant in open-source software. Berkeley DB is written in C with API bindings for many other programming languages. BDB stores arbitrary key/data pairs as byte arrays and supports multiple data items for a single key.
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An Ordered Key-Value Store (OKVS) is a type of data storage paradigm that can support multi-model database. An OKVS is an ordered mapping of bytes to bytes. An OKVS will keep the key-value pairs sorted by the key lexicographic order. OKVS systems provides different set of features and performance trade-offs.
LevelDB is an open-source on-disk key-value store written by Google fellows Jeffrey Dean and Sanjay Ghemawat. [ 2 ] [ 3 ] Inspired by Bigtable , [ 4 ] LevelDB source code is hosted on GitHub under the New BSD License and has been ported to a variety of Unix -based systems, macOS , Windows , and Android .
Voldemort does not try to satisfy arbitrary relations and the ACID properties, but rather is a big, distributed, persistent hash table. [2] A 2012 study comparing systems for storing application performance management data reported that Voldemort, Apache Cassandra, and HBase all offered linear scalability in most cases, with Voldemort having the lowest latency and Cassandra having the highest ...