Denormalization means you (by definition) have duplicate and redundant data in the tables. This certainly requires careful planning around updates to avoid data

Denormalization means you (by definition) have duplicate and redundant data in the tables. This certainly requires careful planning around updates to avoid data corruption. > The number of tables explodes This is IMHO a backwards way to understand normalization. Normalization tell you how many "logical relations" you have in the data - whether you like it or not. If you decide to squash multiple logical relations into the same physical table then you get redundant data (by definition). This might be a fine optimization, but it doesn't reduce the inherent complexity of the data model. It just saves some joins as the cost of more complex update logic.