PDDM: A Database Design Method for Polyglot Persistence

  • Cristofer Zdepski Federal University of Technology – Parana (UTFPR), Address Doutor Washington Subtil Chueire,330-Jardim Carvalho, Ponta Grossa, 84017-220, Parana, Brazil
  • Tarcizio Alexandre Bini Federal University of Technology – Parana (UTFPR), Address Doutor Washington Subtil Chueire,330-Jardim Carvalho, Ponta Grossa, 84017-220, Parana, Brazil
  • Simone Nasser Matos Federal University of Technology – Parana (UTFPR), Address Doutor Washington Subtil Chueire,330-Jardim Carvalho, Ponta Grossa, 84017-220, Parana, Brazil
Keywords: NoSQL, Database Design, Polyglot Persistence, Logical Level Design

Abstract

Databases by Web 2.0 has revealed the limitations of the relational model related to scalability. This led to the emergence of NoSQL databases, with data storage models other than relational ones. These databases propose solutions to such limitations through horizontal scalability and partially compromise data consistency. The combination of multiple data models, called polyglot persistence, extends these solutions by providing resources for the implementation of complex systems that have components with distinct requirements that would not be possible by the use of only one data model in a satisfactory way. However, there are no consolidated methods for the NoSQL database design and neither methods for design systems that apply the polyglot persistence. This work proposes a database design method applied to systems that use polyglot persistence, combining different data models. This method can be applied to the relational model and aggregate-oriented NoSQL data models. The method defines a set of sub-steps based on the existing concepts of database design. The goal is to define a formal process to assist in defining the data models to be used and to transform the conceptual design into a logical design. The method application is demonstrated in some test cases, in order to show its results and applicability for later execution of the physical design of these databases.

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Published
2020-08-06
Section
Articles