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Data Management Strategies for Microservices: Challenges and Future Research Directions

2019 · International Journal of Artificial Intelligence & Digital Transformation · Vol 2, pp. 01-07 · 0 citations

TL;DR

This study combines systematic literature reviews, analysis of open-source applications, and insights from industry practitioners to provide a holistic understanding of the data management landscape in microservices.

Abstract

Microservices architecture has gained significant traction in developing scalable, resilient, and flexible applications by decomposing systems into small, autonomous services. This approach allows for specialized data management strategies tailored to each service's unique requirements. However, the distributed nature of microservices introduces complex data management challenges that are not adequately addressed by traditional software engineering practices alone. This paper investigates the current state of data management within microservices architectures, identifies prevalent challenges, and outlines potential research directions to advance the field. Our study combines systematic literature reviews, analysis of open-source applications, and insights from industry practitioners to provide a holistic understanding of the data management landscape in microservices.

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