我不得不说，应用程序开发人员犯的最大错误是没有正确地规范化数据库。

作为一名应用程序开发人员，我意识到正确的数据库结构、规范化和维护的重要性;我花了无数的时间自学数据库结构和管理。根据我的经验，每当我开始与不同的开发人员合作时，我通常必须重组整个数据库并更新应用程序以适应，因为它通常是畸形的和有缺陷的。

For example, I started working with a new project where the developer asked me to implement Facebook Connect on the site. I cracked open the database to see what I had to work with and saw that every little bit of information about any given user was crammed into one table. It took me six hours to write a script that would organize the table into four or five separate tables and another two to get the app to use those tables. Please, normalize your databases! It will make everything else less of a headache.

这里有一个视频链接，名为“经典数据库开发错误和克服它们的五种方法”，作者是Scott Walz

对于基于sql的数据库:

Not taking advantage of CLUSTERED INDEXES or choosing the wrong column(s) to CLUSTER. Not using a SERIAL (autonumber) datatype as a PRIMARY KEY to join to a FOREIGN KEY (INT) in a parent/child table relationship. Not UPDATING STATISTICS on a table when many records have been INSERTED or DELETED. Not reorganizing (i.e. unloading, droping, re-creating, loading and re-indexing) tables when many rows have been inserted or deleted (some engines physically keep deleted rows in a table with a delete flag.) Not taking advantage of FRAGMENT ON EXPRESSION (if supported) on large tables which have high transaction rates. Choosing the wrong datatype for a column! Not choosing a proper column name. Not adding new columns at the end of the table. Not creating proper indexes to support frequently used queries. creating indexes on columns with few possible values and creating unnecessary indexes. ...more to be added.

使用Excel存储(大量)数据。

我曾见过一些公司拥有数千行并使用多个工作表(由于以前版本的Excel的行数限制为65535)。

Excel非常适合用于报告、数据演示和其他任务，但不应被视为数据库。

相关子查询导致的性能差

大多数情况下，您希望避免相关子查询。如果子查询中存在对外部查询的列的引用，则子查询是相关的。当发生这种情况时，对于返回的每一行至少执行一次子查询，如果在应用包含相关子查询的条件之后应用其他条件，则可以执行更多次。

请原谅这个不自然的示例和Oracle语法，但假设您想要找到自上次商店每天销售额低于10,000美元以来在任何商店中雇用的所有员工。

select e.first_name, e.last_name
from employee e
where e.start_date > 
        (select max(ds.transaction_date)
         from daily_sales ds
         where ds.store_id = e.store_id and
               ds.total < 10000)

本例中的子查询通过store_id与外部查询相关联，并将对系统中的每个员工执行。优化此查询的一种方法是将子查询移动到内联视图。

select e.first_name, e.last_name
from employee e,
     (select ds.store_id,
             max(s.transaction_date) transaction_date
      from daily_sales ds
      where ds.total < 10000
      group by s.store_id) dsx
where e.store_id = dsx.store_id and
      e.start_date > dsx.transaction_date

In this example, the query in the from clause is now an inline-view (again some Oracle specific syntax) and is only executed once. Depending on your data model, this query will probably execute much faster. It would perform better than the first query as the number of employees grew. The first query could actually perform better if there were few employees and many stores (and perhaps many of stores had no employees) and the daily_sales table was indexed on store_id. This is not a likely scenario but shows how a correlated query could possibly perform better than an alternative.

我曾多次看到初级开发人员关联子查询，这通常会对性能产生严重影响。但是，当删除一个相关的子查询时，一定要查看之前和之后的解释计划，以确保您没有使性能变差。

I think the biggest mistakes that all developers and DBAs do is believing too much on conventions. What I mean by that is that convention are only guide lines that for most cases will work but not necessarily always. I great example is normalization and foreign keys, I know most people wont like this, but normalization can cause complexity and cause loss of performance as well, so if there is no reason to move a phone number to a phones table, don't do it. On the foreign keys, they are great for most cases, but if you are trying to create something that can work by it self when needed the foreign key will be a problem in the future, and also you loose performance. Anyways, as I sad rules and conventions are there to guide, and they should always be though of but not necessarily implemented, analysis of each case is what should always be done.