Abstract

Database evolution is a notoriously difficult task, and it is exacerbated by the necessity to evolve database-dependent applications. As science becomes increasingly dependent on sophisticated data management, the need to evolve an array of database-driven systems will only intensify. In this paper, we present an architecture for data-centric ecosystems that allows the components to seamlessly co-evolve by centralizing the models and mappings at the data service and pushing model-adaptive interactions to the database clients. Boundary objects fill the gap where applications are unable to adapt and need a stable interface to interact with the components of the ecosystem. Finally, evolution of the ecosystem is enabled via integrated schema modification and model management operations. We present use cases from actual experiences that demonstrate the utility of our approach.

Date

July 7, 2020

Authors

Robert Schuler, Karl Czajkowski, Mike D'Arcy, Hongsuda Tangmunarunkit, Carl Kesselman

Book

Proceedings of the 32nd International Conference on Scientific and Statistical Database Management

Pages

1-12