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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.
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.
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.
RocksDB is not an SQL database (although MyRocks combines RocksDB with MySQL). Like other NoSQL and dbm stores, it has no relational data model , and it does not support SQL queries. Also, it has no direct support for secondary indexes, however a user may build their own internally using Column Families or externally.
LevelDB stores keys and values in arbitrary byte arrays, and data is sorted by key. It supports batching writes, forward and backward iteration, and compression of the data via Google's Snappy compression library. LevelDB is not an SQL database. Like other NoSQL and dbm stores, it does not have a relational data model and it does not support ...
A column consists of a (unique) name, a value, and a timestamp. A column of a distributed data store is a NoSQL object of the lowest level in a keyspace. It is a tuple (a key–value pair) consisting of three elements: Unique name: Used to reference the column; Value: The content of the column.
Bigtable development began in 2004. [1] It is now used by a number of Google applications, such as Google Analytics, [2] web indexing, [3] MapReduce, which is often used for generating and modifying data stored in Bigtable, [4] Google Maps, [5] Google Books search, "My Search History", Google Earth, Blogger.com, Google Code hosting, YouTube, [6] and Gmail. [7]
Dynamo is a set of techniques that together can form a highly available key-value structured storage system [1] or a distributed data store. [1] It has properties of both databases and distributed hash tables (DHTs). It was created to help address some scalability issues that Amazon experienced during the holiday season of 2004. [2]