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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.
RocksDB, like LevelDB, stores keys and values in arbitrary byte arrays, and data is sorted byte-wise by key or by providing a custom comparator. RocksDB provides all of the features of LevelDB, plus: Transactions [16] Backups [17] and snapshots [18] Column families [19] Bloom filters [20] Time to live (TTL) support [21] Universal compaction [22]
AQL, HTTP, Java, JavaScript, PHP, Go, Scala, .Net, Python, Ruby Business Source License 1.1 ArangoDB is a transactional native multi-model database supporting two major NoSQL data models (graph and document [1]) with one query language. Written in C++ and optimized for in-memory computing.
Berkeley DB 1.x releases focused on managing key/value data storage and are referred to as "Data Store" (DS). The 2.x releases added a locking system enabling concurrent access to data. This is what is known as "Concurrent Data Store" (CDS). The 3.x releases added a logging system for transactions and recovery, called "Transactional Data Store ...
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 ...
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 ...
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.
A triplestore or RDF store is a purpose-built database for the storage and retrieval of triples [1] through semantic queries.A triple is a data entity composed of subject–predicate–object, like "Bob is 35" (i.e., Bob's age measured in years is 35) or "Bob knows Fred".