HyDRa: A Framework for Modeling, Manipulating and Evolving Hybrid Polystores

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Abstract

Data-intensive system evolution is a complex and error-prone process, as most evolution scenarios impact several interdependent artefacts such as the application code, the data structures or data instances. This process is becoming even more challenging with the emergence of heterogeneous database
architectures, commonly called hybrid polystores, that rely on a combination of several, possibly overlapping relational and NoSQL databases. This paper presents HyDRa, a framework aiming to facilitate the evolution of polystores thanks to automatically generated data access APIs. For a given polystore, a
conceptual API can be derived from the conceptual schema of the polystore and its correspondences with the physical schemas of the underlying databases. Applications built on top of the generated API are then protected from future schema and data reconfiguration changes applied to the polystore. Furthermore,
HyDRa automatically enforces cross-database data integrity constraints and does not require developers to master multiple data models and query languages. This paper presents HyDRa and demonstrates its main features based on open-source datasets and realistic use cases.
Original languageEnglish
Title of host publicationProceedings of the 29th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2022)
PublisherIEEE Computer society
Publication statusAccepted/In press - 2022

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