它将数据储存在一个平面地址空间中，这就像一个完全反规范化的数据仓库。
It stores its data in a flat address space, much like a completely de-normalized data warehouse.
区别在于，在处理AppEngine数据存储时，您必须尽早且经常进行反规范化。
The difference is, when dealing with the App Engine datastore, you must de-normalize early and often.
不过，当要求实现更高的性能时，则需要创建物化视图来反规范化(de - normalize)数据。
However, when high performance is required, materialized views are created to de-normalize the data.
如果您确实打算反规范化，那么一定要为此制作完整文档：较详细地描述您所采取的反规范化步骤背后的原因。
If you do decide to de-normalize, be sure to document this thoroughly: describe in some detail, the reasoning behind the de-normalization steps that you took.
而更改表的设计，或修改用户需求，抑或修改反规范化(de - normalizing)表，都不是很有吸引力的选择。
Changing the table design, or modifying user requirements, or de-normalizing the tables, are usually less attractive options.
而将一个表 反规范化（de-normalize）的意思是，违反该表之前遵从的一种或多种范式，从而修改规范化的设计。
To de-normalize a table means that you modify the normalized design by violating one or more of the normal forms to which the table had previously conformed.
本文在简要介绍了数据库中反规范化的应用后，详细地举出了一个用反规范化设计的数据库来讨论如何通过反规范化进行数据库设计优化。
This paper introduces the appliance of anti-normalization in database design, which gives some examples based on the implement of anti-normalization to optimize the database design.
从理论上来说，总是建议您保证数据的规范化；但是在实践中，过度的规范化(或者没有恰当反规范化的规范化)会导致对数据检索连接的依赖性。
Data normalization is always recommended in theory, but in practice over-normalization (or normalization without appropriate de-normalization) lead to reliance on joins for data retrieval.
从理论上来说，总是建议您保证数据的规范化；但是在实践中，过度的规范化(或者没有恰当反规范化的规范化)会导致对数据检索连接的依赖性。
Data normalization is always recommended in theory, but in practice over-normalization (or normalization without appropriate de-normalization) lead to reliance on joins for data retrieval.
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