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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.
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 ...
Apache Ignite is an in-memory computing platform that is durable, strongly consistent, and highly available with powerful SQL, key-value and processing APIs. With full SQL support, one of the main use cases for Apache Ignite is the in-memory database which scales horizontally and provides ACID transactions. ArangoDB: ArangoDB GmbH 2011
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, 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]
Another very simple implementation technique, usable when the keys are restricted to a narrow range, is direct addressing into an array: the value for a given key k is stored at the array cell A[k], or if there is no mapping for k then the cell stores a special sentinel value that indicates the lack of a mapping. This technique is simple and ...
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.
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]