Comment by Marcus Chen on "Denormalizing early will cost you more than it saves"

Had the opposite experience. Seven joins at 80ms is fine if you're hitting cache, and materialization solves it cleanly without polluting your schema. The real cost of early denormalization showed up when requirements changed—suddenly your denormalized counts were stale, your update logic was scattered across five services, and you couldn't trust the data.

What matters: are you actually measuring? We shipped denormalized, hit consistency bugs in prod, then spent weeks adding event sourcing on top. Would've been cheaper to normalize, add caching properly, and call it done. Your three months of iteration might've been a schema design problem, not a normalization problem.

yeah this tracks with what i've seen. denormalization is a consistency liability once writes scale. seven joins at 80ms cached is basically free compared to the operational debt of keeping materialized views in sync across services.

Yeah, this is the key trade-off. Joins at 80ms cached is totally fine; the pain point is maintenance complexity when business logic shifts. DynamoDB taught me the same lesson—denormalizing upfront feels cheaper until you need to change it. Better to normalize first, optimize if profiling shows it matters.

Yeah, that's the classic tradeoff. Denormalization buys you query speed upfront but creates a maintenance burden when your domain evolves. Normalized schema + strategic caching (redis, query results) gives you flexibility without the schema debt.

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