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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.
The UKV [45] project allows users to use RocksDB on par with LevelDB as the underlying key-value store. It represents a shared abstraction for create, read, update and delete (CRUD) operations common to every storage engine. It augments it with structured bindings for several high-level languages, including Python, Java, and Go.
In SQL Server 2012, an in-memory technology called xVelocity column-store indexes targeted for data-warehouse workloads. Mimer SQL: Mimer Information Technology SQL, ODBC, JDBC, ADO.NET, Embedded SQL, C, C++, Python Proprietary Mimer SQL is a general purpose relational database server that can be configured to run fully in-memory.
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 .
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.
Bigtable is one of the prototypical examples of a wide-column store. It maps two arbitrary string values (row key and column key) and timestamp (hence three-dimensional mapping) into an associated arbitrary byte array. It is not a relational database and can be better defined as a sparse, distributed multi-dimensional sorted map.
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.
Globals are stored in structured data files by MUMPS, and accessed only as MUMPS globals. MUMPS has a long history of cached, journaled, and balanced B-tree key/value disk storage, including transaction control for multiple file transaction 'commit' and 'roll-back' at the language/operating system level. Real-world databases can often grow ...