The history of the relational database has been one of continual adversity: initially, many claimed that mathematical set-based models could never be the basis for e?cient database implementations; later, aspiring object oriented databases claimed they would remove the ?middle man? of relational databases from the OO design and persistence process. In all of these cases, through a combination of sound concepts, elegant implementation, and general applicability, relational databases have become and remained the lingua franca of data storage and manipulation.
Most recently, a new contender has arisen to challenge the supremacy of relational databases. Referred to generally as ?non-relational databases? (among other names), this class of storage engine seeks to break down the rigidity of the relational model, in exchange for leaner models that can perform and scale at higher levels, using various models (including key/value pairs, sharded arrays, and document-oriented approaches) which can be created and read e?ciently as the basic unit of data storage. Primarily, these new technologies have arisen in situations where traditional relational database systems would be extremely challenging to scale to the degree needed for global systems (for example, at companies such as Google, Yahoo, Amazon, LinkedIn, etc., which regularly collect,store and analyze massive data sets with extremely high transactional throughput and low latency). As of this writing, there exist dozens of variants of this new model, each with di?erent capabilities and trade-o?s, but all with the general property that traditional relational design ? as practiced on relational database management systems like Oracle, Sybase, etc. ? is neither possible nor desired
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