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Mortadelo: Automatic generation of NoSQL stores from platform-independent data models
Mortadelo: تولید خودکار فروشگاههای NoSQL از مدلهای داده مستقل از پلتفرم-2020 In the last decade, several NoSQL systems have emerged as a response to the scalability problems
manifested by classical relational databases when used in Big Data contexts. These NoSQL systems
appeared first as physical-level solutions, initially lacking any design methodologies. After this initial
batch of systems, several design methodologies for NoSQL have been recently created. Nevertheless,
most of these methodologies target just one NoSQL paradigm. In addition, as each methodology uses a
different conceptual modeling approach, NoSQL database designers would need to remake conceptual
models as they switch from one NoSQL paradigm to another. Moreover, most of these design processes
provide just a set of design heuristics and guidelines that database designers need to apply manually,
which can be a time-consuming and error-prone process. To overcome these limitations, this article
presents Mortadelo, a model-driven NoSQL database design process where, from a high-level conceptual
model, independent of any specific NoSQL paradigm, an implementation for a concrete NoSQL database
system can be automatically generated. Moreover, this database generation process can be customized,
so that some design trade-offs can be managed differently according to each context needs. We
evaluated Mortadelo’s capabilities by generating database implementations for several typical NoSQL
case studies. In these cases, Mortadelo was able to generate implementations for the Cassandra and
MongoDB NoSQL systems from the same conceptual data model. These implementations were similar
to the ones generated by design methodologies specifically developed for a single paradigm. Therefore,
design quality is not sacrificed by our approach in favor of generality. Keywords: NoSQL | Database design | Data modeling | Model-driven engineering | Column family stores | Document stores |
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