Updating "denormalized" aggregates with "duplicates": MongoDB vs. PostgreSQL

TL;DR: In database-centric development, duplication is dangerous because, in shared, normalized relational databases, it leads to update anomalies. In contrast, in DDD, aggregates own their data, so duplication is intentional and updates are controlled by the application. MongoDB supports this approach with fine-grained updates on document arrays and fields, while PostgreSQL JSONB often requires rewriting entire documents, which can make normalization more appealing. As a result, duplication itself is not the core problem—what matters is who owns the data and how updates are optimized. In Domain-Driven Design (DDD) , aggregates define consistency boundaries , leading to an intentionally denormalized model. In a relational database, this can feel counterintuitive due to concerns over data duplication and update anomalies. In a shared SQL database with direct/unrestricted access (accepting ad-hoc SQL queries across the entire schema), normalization is often preferred to guarantee a singl