Data denormalization is broken
I&#x27;m usually the guy arguing against microservices, but I think this is a good example of why they shine.  It&#x27;s much easier to manage the updating of these synthesized numbers if you have a discrete service that limits the things you can do at a higher level.  So instead of worrying about who is updating the data store directly, you push it up to a higher service-level interface where you have a finite list of operations that are supported, and the scope is small enough that one architect can understand the system in its entirety and make smart decisions about how to compute&#x2F;store&#x2F;cache these synthesized data.<p>That said, if you have less than 10 engineers this shouldn&#x27;t even be thinking about this.  Way too many young engineers get hung up on scalability when they don&#x27;t even have anything on the horizon that will require scaling.  Couple that with a general ignorance of SQL because it&#x27;s old and boring, and not realizing how much performance you can eke out of a well tuned RDBMS with proper schema and queries.  A SQL DB is an incredible hedge against an uncertain future, keep your data tidy and you can keep pivoting until you find something you actually <i>have</i> to scale.