2016/06/18 by Jeremy Kepner, Vijay Gadepally, Dylan Hutchison +4
Computer Science · #Advanced Database Systems and Queries #Associative array #Associative property #Cloud Computing and Resource Management #Data exchange #Graph Theory and Algorithms #Key (lock) #Reflection (computer programming) #Relational database #SQL #The Internet #cs.DB #cs.DC #cs.PL
paper · pdf · doi:10.1109/hpec.2016.7761647
9 pages; 6 figures; accepted to IEEE High Performance Extreme Computing (HPEC) conference 2016
arxiv created 2016/06/18 · openalex created_date 2016/07/22 · openalex publication_date 2016/09/01 · arxiv updated 2016/12/13 · openalex updated_date 2026/08/05
The success of SQL, NoSQL, and NewSQL databases is a reflection of their ability to provide significant functionality and performance benefits for specific domains, such as financial transactions, internet search, and data analysis. The BigDAWG polystore seeks to provide a mechanism to allow applications to transparently achieve the benefits of diverse databases while insulating applications from the details of these databases. Associative arrays provide a common approach to the mathematics found in different databases: sets (SQL), graphs (NoSQL), and matrices (NewSQL). This work presents the SQL relational model in terms of associative arrays and identifies the key mathematical properties that are preserved within SQL. These properties include associativity, commutativity, distributivity, identities, annihilators, and inverses. Performance measurements on distributivity and associativity show the impact these properties can have on associative array operations. These results demonstrate that associative arrays could provide a mathematical model for polystores to optimize the exchange of data and execution queries.