Software Architectures and Patterns for Persistence in Heterogeneous Data-Intensive Systems

Software engineers are faced with a variety of difficult choices when selecting appropriate technologies on which to base a software system. As the typical software user has become accustomed to systems being \u22on-demand\u22 and \u22always- available,\u22 the software engineer is more concerned than ever before about the issues of system scalability, availability, and durability. In the absence of expertise in distributed systems, architectural decisions become complex, slowing feature development and introducing error. Software engineering is in need of robust patterns and tools that increase the accessibility of specialized technologies developed for the completion of specialized tasks. This dissertation describes my existing work related to the challenges of domain modeling and data-access in large- scale, heterogeneous data-intensive systems and extends this work to include novel architectures for utilizing multiple large-scale data stores effectively. This research focuses on increasing the accessibility and flexibility of these data stores, which typically afford scalability, availability, and durability at the cost of added complexity for the application developer. The resulting architecture and associated implementation alleviates common challenges faced by small and medium software enterprises during the development of heterogeneous data-intensive software applications