Associative Array Model of SQL, NoSQL, and NewSQL Databases

TL;DR

This paper proposes an associative array mathematical model to unify SQL, NoSQL, and NewSQL databases, enabling optimized data exchange and query execution across diverse database systems.

Contribution

It introduces a formal associative array framework for different database types and analyzes their mathematical properties to improve polystore performance.

Findings

Associative arrays unify different database models mathematically.

Key properties like associativity and distributivity impact performance.

Results suggest associative arrays can optimize polystore data exchange.

Abstract

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.