^ A document data model on FoundationDB, implementing MongoDB® wire protocol: FoundationDB/fdb-document-layer, FoundationDB,, retrieved.^ A record-oriented store built on FoundationDB., FoundationDB,, retrieved.^ "How FoundationDB Powers Snowflake Metadata Forward | Snowflake Blog".^ "Comparing new RocksDB and MMFiles storage engines".^ "sophia - modern transactional key-value/row storage library".bsddb - Interface to Berkeley DB library - Python 2.7.17 documentation". ^ "BerkeleyDB & other distributed high performance key/value databases - High Scalability -".Document database, that mimics MongoDB API,Īll those abstraction can co-exist with the same OKVS database and when ACID is supported, the operations happens with the guarantees offered by the transaction system.įeature Matrix Comparison of several Ordered Key-Value Stores.Tuple Stores, also known as Triple Store or Quad Store but also Generic Tuple Store,.Record Database, also known as Row store databases, they behave similarly to what is dubbed RDBMS,.The following abstraction or databases were built on top Ordered Key-Value Stores: It allows to create secondary representation, also called indices, that will allow to speed up queries. When taking advantage of the ordered nature of the key space, one can query ranges of keys that have particular pattern.ĭe-normalization, as in, repeating the same piece of data in multiple subspace is common practice. The idea is to construct keys, that takes advantage of the ordered nature of the top level key space. One can construct key spaces to build higher level abstractions. In FoundationDB, it is called the tuple layer. That is, one can work with an Ordered Key-Value Store without having to fiddle with bytes directly. There are algorithms that encode basic data types (string, integer, float) and composition of those data types inside sorted containers like tuples, lists or vectors that preserve their "natural" ordering. JanusGraph, a property graph database, has both a Berkeley DB backend and FoundationDB backend. Some NewSQL databases are supported by Ordered Key-Value Stores. Another notable use of OKVS paradigm is the multi-model database system called ArangoDB based on RocksDB. Other notable implementation of the OKVS paradigm are Sophia and SQlite3 LSM extension.
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In 2014, WiredTiger, successor of Berkeley DB was acquired by MongoDB and is since 2019 the primary backend of MongoDB database. There is also Google's LevelDB that was forked by Facebook in 2012 as RocksDB. In 2011, LMDB was created to replace Berkeley DB in OpenLDAP.
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In 2009, Tokyo Cabinet was released that was superseded by Kyoto Cabinet that support both transaction and ordered keys. It was included in Python standard library until 2.7. Berkeley DB was said to be very fast and made its way into various commercial product. Later in 1991, Berkeley DB was released that featured a B-Tree backend that allowed the keys to stay sorted.
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The origin of Ordered Key-Value Store stems from the work of Ken Thompson on dbm in 1979.