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  2. Key–value database - Wikipedia

    en.wikipedia.org/wiki/Keyvalue_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.

  3. Amazon DynamoDB - Wikipedia

    en.wikipedia.org/wiki/Amazon_DynamoDB

    Amazon DynamoDB is a managed NoSQL database service provided by Amazon Web Services (AWS). It supports key-value and document data structures and is designed to handle a wide range of applications requiring scalability and performance.

  4. Dynamo (storage system) - Wikipedia

    en.wikipedia.org/wiki/Dynamo_(storage_system)

    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]

  5. Valkey - Wikipedia

    en.wikipedia.org/wiki/Valkey

    Valkey is an open-source in-memory storage, used as a distributed, in-memory key–value database, cache and message broker, with optional durability. [8] Because it holds all data in memory and because of its design, Valkey offers low-latency reads and writes, making it particularly suitable for use cases that require a cache.

  6. Redis - Wikipedia

    en.wikipedia.org/wiki/Redis

    According to monthly DB-Engines rankings, Redis is often the most popular key–value database. [10] Redis has also been ranked the #4 NoSQL database in user satisfaction and market presence based on user reviews, [41] the most popular NoSQL database in containers, [42] and the #4 Data store of 2019 by ranking website stackshare.io. [43]

  7. Voldemort (distributed data store) - Wikipedia

    en.wikipedia.org/wiki/Voldemort_(distributed...

    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 ...

  8. Wide-column store - Wikipedia

    en.wikipedia.org/wiki/Wide-column_store

    A wide-column store (or extensible record store) is a type of NoSQL database. [1] It uses tables, rows, and columns, but unlike a relational database, the names and format of the columns can vary from row to row in the same table. A wide-column store can be interpreted as a two-dimensional key–value store. [1]

  9. Comparison of structured storage software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_structured...

    Key-value & Hierarchical & Document Yes Yes Yes Yes likely Java: Apache, Roy Fielding, Day Software: Apache 2.0: Berkeley DB/Dbm 1.x Key-value Yes No No No No C: old school Various Berkeley DB Sleepycat/Oracle Berkeley DB 5.x Key-value Yes Yes Yes Yes No C, C++, or Java dbm, Sleepycat/Oracle dual GPL-like Sleepycat License Apache Cassandra: Key ...