是的，当然。每当有更改时，我们生成PostgreSQL模式的转储并签入。它已经救了我们很多次，而我才上任几个月。

我已经在http://dbdeploy.com/上使用了ThoughtWorks的dbdeploy工具。它鼓励使用迁移脚本。在每个版本中，我们将更改脚本合并到一个文件中，以简化理解，并允许dba“支持”更改。

The most successful scheme I've ever used on a project has combined backups and differential SQL files. Basically we would take a backup of our db after every release and do an SQL dump so that we could create a blank schema from scratch if we needed to as well. Then anytime you needed to make a change to the DB you would add an alter scrip to the sql directory under version control. We would always prefix a sequence number or date to the file name so the first change would be something like 01_add_created_on_column.sql, and the next script would be 02_added_customers_index. Our CI machine would check for these and run them sequentially on a fresh copy of the db that had been restored from the backup.

我们还准备了一些脚本，开发人员可以用一个命令将本地db重新初始化到当前版本。

我们在源代码控制下有创建/修改脚本。至于数据库本身，当您有数百个表并且每分钟处理大量数据时，对所有数据库进行版本化将是CPU和HDD的杀手。这就是为什么在我看来，备份仍然是控制数据的最佳方式。

A big problem, often overlooked, is that for larger web based systems, it is required to have a transitional period or bucket testing approach to making new releases. This makes it essential to have both rollback and a mechanism for supporting both the old and new schema in the same DB. This requires a scaffolding approach (made populist by the Agile DB folks). In this scenario, lack of process in DB source control can be a total disaster. You need old schema scripts, new schema scripts and a set of intermediate scripts, as well as a tidy up, once the system is fully on the new version (or rolled back).

需要的不是从头开始重新创建模式的脚本，而是一种基于状态的方法，在这种方法中，您只需要脚本将DB从一个版本移动到另一个版本，向前或向后移动到所需的状态。您的DB变成了一系列状态脚本，可以轻松地对其进行源代码控制，并与源代码的其余部分一起标记。

任何数据库接口代码都应该进入版本控制(存储过程、函数等)。

对于结构和数据，这是一个判断。我个人对我的数据库保持一个干净的结构模板，但由于它们的大小，不将它们存储在版本控制中。但是将它存储在版本控制中是非常有益的，即使对于只有历史记录也是如此。