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Explains when EF Core compiled queries help, what they do not fix, and how to measure their value.
Explains how query tags, request correlation, and telemetry help connect slow SQL back to code paths.
Explains when set-based EF Core updates are better than loading entities and where lifecycle behavior can differ.
Explains referential integrity, cascade delete trade-offs, restrict behavior, soft deletes, and operational safety.
Explains aggregate queries, grouping keys, filters before and after aggregation, and business-count correctness.
Connects HTTP preconditions to atomic database concurrency checks and honest 412 or 428 API behavior.
Prevents lost updates with an original rowversion predicate, maps zero affected rows to an explicit conflict, and defines user, retry, aggregate, and API precondition behavior.
Makes consumer-side deduplication atomic with the business change while supporting concurrent delivery, retention, replay, and failed processing.
Makes business uniqueness race-safe with the exact database key, while handling normalization, tenant scope, nulls, soft deletion, rollout cleanup, and stable API conflicts.
Uses ROW_NUMBER with deterministic partition ordering to return one complete latest row per group, then evaluates index support, tie semantics, scale, and read-model alternatives.
Runs a migration-backed pytest integration test against PostgreSQL and proves case-insensitive email uniqueness.
Runs a Spring Boot integration test against PostgreSQL and proves a migration-backed database constraint at flush time.
Separates transaction-phase callbacks inside one process from durable database-backed publication across process failure.