David Garlan recently asked me what I thought about data modeling and its relationship to software architecture. I’m including the answer here because it was effective at articulating some of my philosophical assumptions about software architecture that are not shared by all researchers and practitioners.
Since data(base) modeling commits to a data representation, it hurts your ability to zoom out. It also introduces discussions of N-th normal forms and efficient use of varchar vs. string(20). What MAp calls “information modeling” commits you to the existence and relationship between types, but not their concrete data representations, which allows it to uncover design defects related to the problem domain.
Data modeling is a large and specific concern at companies, because the data and its schema may span applications and outlive all of them. It may have a place in architecture descriptions simply because its significance to companies, but I am unconvinced that it is an architectural style or at the same level of abstraction as the rest of the software architecture ideas.
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