Building Evolutionary Architectures, 2nd Edition

Chapter 6. Evolutionary Data

Relational and other types of data stores are ubiquitous in modern software projects, a form of coupling that is often more problematic than architectural coupling. Data teams are generally not as accustomed to engineering practices such as unit testing and refactoring (which is gradually improving). Also, databases often become integration points, making data teams reluctant to make changes due to potential rippling side effects.

Data is an important dimension to consider when creating an evolvable architecture. Architectures like microservices require much more architectural consideration of data partitioning, dependencies, transactionality, and a host of other issues that were formerly only the realm of data teams. It is beyond the scope of this book to cover all the aspects of evolutionary database design. Fortunately, our co-author Pramod Sadalage, along with Scott Ambler, wrote Refactoring Databases, subtitled Evolutionary Database Design. We cover only the parts of database design that impact evolutionary architecture and encourage readers to read that book.

Evolutionary Database Design

Evolutionary design in databases occurs when developers can build and evolve the structure of the database as requirements change over time. Database schemas are abstractions, similar to class hierarchies. As the underlying real world changes, those changes must be reflected in the abstractions developers and data teams build. Otherwise, the abstractions gradually ...