Data-Oriented Architecture. There’s a little-known pattern in software architecture that deserves more attention. Data-Oriented Architecture was first described by Rajive Joshi in a 2007 whitepaper at RTI, and again in 2017 by Christian Vorhemus and Erich Schikuta at the University of Vienna in this iiWAS paper. DOA is an inversion of the traditional dichotomy between a monolithic binary and data store (monolithic architecture) on the one hand, and small, distributed, independent binaries each with their own data stores (microservices, and service-oriented architecture) on the other. In data-oriented architecture, a monolithic data store is the sole source of state in the system, which is being acted on by loosely-coupled, stateless microservices.
I was lucky that my former employer also fell upon this unusual architectural choice. It was a reminder that things can be done differently. Data-oriented architecture isn’t a silver bullet by any means; it has its own unique set of costs and benefits. What I did find, though, is that a lot of large companies and ecosystems are stuck at exactly the type of bottleneck that data-oriented architecture is meant to resolve.