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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 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 .
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 ...
Object storage (also known as object-based storage [1] or blob storage) is a computer data storage approach that manages data as "blobs" or "objects", as opposed to other storage architectures like file systems, which manage data as a file hierarchy, and block storage, which manages data as blocks within sectors and tracks. [2]
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]
A name–value pair, also called an attribute–value pair, key–value pair, or field–value pair, is a fundamental data representation in computing systems and applications. Designers often desire an open-ended data structure that allows for future extension without modifying existing code or data.
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]
Bigtable development began in 2004. [1] It is now used by a number of Google applications, such as Google Analytics, [2] web indexing, [3] MapReduce, which is often used for generating and modifying data stored in Bigtable, [4] Google Maps, [5] Google Books search, "My Search History", Google Earth, Blogger.com, Google Code hosting, YouTube, [6] and Gmail. [7]