From my experience its always better to avoid using FKs in Database Critical Applications. I would not disagree with guys here who say FKs is a good practice but its not practical where the database is huge and has huge CRUD operations/sec. I can share without naming ... one of the biggest investment bank of doesn't have a single FK in databases. These constrains are handled by programmers while creating applications involving DB. The basic reason is when ever a new CRUD is done it has to effect multiple tables and verify for each inserts/updates, though this won't be a big issue for queries affecting single rows but it does create a huge latency when you deal with batch processing which any big bank has to do as daily tasks.

最好避免fk，但它的风险必须由程序员来处理。

我一直认为不用它们是懒惰的表现。我被教导应该一直这样做。但后来，我没有听乔尔的讨论。他也许有充分的理由，我不知道。

One time when an FK might cause you a problem is when you have historical data that references the key (in a lookup table) even though you no longer want the key available. Obviously the solution is to design things better up front, but I am thinking of real world situations here where you don't always have control of the full solution. For example: perhaps you have a look up table customer_type that lists different types of customers - lets say you need to remove a certain customer type, but (due to business restraints) aren't able to update the client software, and nobody invisaged this situation when developing the software, the fact that it is a foreign key in some other table may prevent you from removing the row even though you know the historical data that references it is irrelevant. After being burnt with this a few times you probably lean away from db enforcement of relationships. (I'm not saying this is good - just giving a reason why you may decide to avoid FKs and db contraints in general)

我同意前面的答案，因为它们对维护数据一致性很有用。然而，Jeff Atwood几周前发表了一篇有趣的文章，讨论了规范化和一致性数据的利弊。

简而言之，在处理大量数据时，非规范化数据库可以更快;你可能不关心精确的一致性取决于应用程序，但它迫使你在处理数据时更加小心，因为DB不会。

“在添加记录之前，检查对应的记录是否存在于另一个表中”是业务逻辑。

这里有一些你不希望在数据库中使用它的原因:

If the business rules change, you have to change the database. The database will need to recreate the index in a lot of cases and this is slow on large tables. (Changing rules include: allow guests to post messages or allow users to delete their account despite having posted comments, etc). Changing the database is not as easy as deploying a software fix by pushing the changes to the production repository. We want to avoid changing the database structure as much as possible. The more business logic there is in the database the more you increase the chances of needing to change the databae (and triggering re-indexing). TDD. In unit tests you can substitute the database for mocks and test the functionality. If you have any business logic in your database, you are not doing complete tests and would need to either test with the database or replicate the business logic in code for testing purposes, duplicating the logic and increasing the likelyhood of the logic not working in the same way. Reusing your logic with different data sources. If there is no logic in the database, my application can create objects from records from the database, create them from a web service, a json file or any other source. I just need to swap out the data mapper implementation and can use all my business logic with any source. If there is logic in the database, this isn't possible and you have to implement the logic at the data mapper layer or in the business logic. Either way, you need those checks in your code. If there's no logic in the database I can deploy the application in different locations using different database or flat-file implementations.

我不得不在这里第二多的评论，外键是必要的项目，以确保你有完整的数据。ON DELETE和ON UPDATE的不同选项将允许你绕过一些人们在这里提到的关于它们的使用的“下降”。

我发现在我99%的项目中，我会使用FK来加强数据的完整性，然而，在很少的情况下，我的客户必须保留他们的旧数据，不管它有多糟糕....但后来我花了很多时间写代码，只得到有效的数据，所以它变得毫无意义。