Ben Johnston

This continues my series on auditing SQL Server. The fist parts covered discovery and documentation, server level hardware audits and SQL Server engine level audits. This section examines database configuration audits. As with the previous audit sections, the boundaries for the audit can be blurry. I try to stick to configuration items only, but I also discuss some code smells and items that can impact performance or might be covered in a code review. You will need to determine the scope of your audits and how much you want to cover in this portion of the audit.

An entire post on choosing the correct data types either seems like overkill or much needed and overdue. The perspective might vary based on the databases you’ve worked with recently. I decided to write this after seeing some code with data type decisions that I would classify as questionable. There are many decisions in technology that can be ambiguous, but the correct date type should be based on business rules and a set of technical guidelines. I am going to share my thought process for deciphering the correct type here.

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SQL is easy to start writing. The basic syntax to start returning data is very simple. This low threshold for starting SQL hides some of the nuances that divide efficient queries from inefficient queries. As your SQL gets more complicated and you need to join multiple tables and perform intricate operations on the data, it is important to understand the basics of how queries are processed and how your query decisions impact performance.

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I recently had an interesting production SQL Server issue that turned out to be very easy to fix. The fix doesn’t fit every workload or server, but for the limited use cases described below, it’s a simple configuration change. The general best practice for server level configurations is to leave things at default, unless there is a specific reason for changing the settings. This will outline a use case for using memory-optimized tempdb metadata.