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You have that backwards. Denormalization is a performance optimization. By duplicating data you reduce the need for costly joins at the expense of data consis
by ipaddr 5y ago
You have that backwards.
Denormalization is a performance optimization. By duplicating data you reduce the need for costly joins at the expense of data consistency.
- dachryn 5y agoboth of you can be wrong, but in practice its more like: finding the right level of normalization is a performance optimization.
- funcDropShadow 5y agoDenormalization is only a performance optimization if it matches exactly to your queries. If your data is denormalized in some way, but later on you discover you want to query it differently, it may be way more expensive to query it then. Even if you know beforehand that you want to access the data in multiple different ways and you denormalize it for all those ways, it might be faster to use normalization because of better memory-locality. So, there are a lot of tradeoffs.