In computing, NoSQL (Not Only SQL) is a term used to designate database management systems that differ from classic relational database management systems in some way. These data stores may not require fixed table schemas, and usually avoid join operations and typically scale horizontally. Academics and papers typically refer to these databases as structured storage,[1][2][3][4] a term that would include classic relational databases as a subset.

Notable production implementations include Google's BigTable, Amazon's Dynamo and Apache Cassandra.

Typical modern relational databases have shown poor performance on certain data-intensive applications, including indexing a large number of documents, serving pages on high-traffic websites, and delivering streaming media.[7] Typical RDBMS implementations are tuned either for small but frequent read/write transactions or for large batch transactions with rare write accesses. NoSQL on the other hand, services heavy read/write workloads.[7] Real-world NoSQL deployments include Digg's 3 TB for green badges (markers that indicate stories upvoted by others in a social network),[8]Facebook's 50 TB for inbox search, and eBay's 2 PB overall data.

NoSQL architectures often provide weak consistency guarantees, such as eventual consistency, or transactions restricted to single data items. Some systems, however, provide full ACID guarantees, in some instances by adding a supplementary middleware layer (e.g., CloudTPS).[9] Two systems have been developed that provide snapshot isolation for column stores: Google's Percolator system based on BigTable,[10] and a transactional system for HBase developed at the University of Waterloo.[11] These systems, developed independently, use similar concepts to achieve multi-row distributed ACID transactions with snapshot isolation guarantee for the underlying column store, without the extra overhead of data management, middleware system deployment, or maintenance introduced by the middleware layer.

Several NoSQL systems employ a distributed architecture, with the data held in a redundant manner on several servers, often using a distributed hash table. In this way, the system can readily scale out by adding more servers, and failure of a server can be tolerated.[12]

Some NoSQL advocates[who?] promote very simple interfaces such as associative arrays or key-value pairs. Other systems, such as native XML databases, promote support of the XQuery standard.[citation needed] Newer systems such as CloudTPS also support join queries.[13]