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To date, most large corporations still have their core solutions on relational databases but only use non-relational (i.e. NoSQL) database management systems (DBMS) for their non-core systems that favour availability and scalability through partitioning while trading off consistency. NoSQL systems are built based on the CAP (i.e., Consistency, Availability and Partitioning) database theorem, which trades off one of these features while maintaining the others. The need for systems availability and scalability drives the use of NoSQL, while the lack of consistency and robust query engines as obtainable in relational databases, impede their usage. To mitigate these drawbacks, researchers and companies like Amazon, Google, and Facebook run ’SQL over NoSQL’ systems such as Dynamo, Google’s Spanner, Memcache, Zidian, Apache Hive and SparkSQL. These systems create a query engine layer over NoSQL systems but suffer from data redundancy and lack consistency obtainable in relational DBMS. Also, their query engine is not relational complete because they cannot process all relational algebra-based queries as obtainable in a relational database. In this paper, we present a ’Unique NoSQL over SQL Database’ (UniqueNOSD) system, an extension of NOSD and an inverse of existing approaches. This approach is motivated by the need for existing systems to fully deploy NoSQL data store functionalities without the limitation of building an extra SQL layer for querying. To allow appropriate storage and retrieval of data on document-based NoSQL databases without data redundancy and inconsistency while encouraging both horizontal and vertical partitioning, we propose NoSQL over SQL Block as a Value (
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1 University of Windsor, School of Computer Science, Windsor, Canada (GRID:grid.267455.7) (ISNI:0000 0004 1936 9596)