architecting-data

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Data architecture patterns covering read-side optimization (replicas, materialized views, CQRS, CDC, event sourcing), domain-based decomposition, polyglot persistence, and caching strategies (cache-aside, read-through, write-through, write-around). Use when designing data flow architecture, choosing read scalability strategies, or implementing caching for enterprise systems. For microservices patterns (Saga, granularity), use architecting-microservices instead. For DDD domain modeling, use applying-domain-driven-design instead. For database engine internals, use understanding-database-internals instead. For relational DB schema design, use designing-relational-databases instead. For GCP-specific data services (BigQuery, Dataflow, Dataproc), use developing-google-cloud instead.