Below is a round-up of this month’s participating blog posts in order of the comments left on the original announcement.
Rob Farley (blog|@rob_farley) got us kicked off with his entry Join Effects With UPDATE. Rob reminds us of some of the basics of the UPDATE statement and talks about some of the dangers of how you write the statement that you might not be aware of. There was a potential danger he called out that I was not aware of. In fact, I had not even considered the possibility. Read his post to see what I mean
Koen Verbeeck (blog|@Ko_Ver) gives us a good reason to give temporal tables a look in his post T-SQL Tuesday #74: Be the Change. Koen’s post also provided my favorite line of the month when he opined on Change Data Capture (CDC) and Change Tracking (CT).
In some very rare cases, you can actually use change data capture or change tracking on the source system.
Mickey Stuewe (blog|@SQLMickey), who is a #SQLNewBlogger, chimes in with her post T-SQL Tuesday #74 – Knowing When Data Changes Occur in Standard Edition. Mickey gives us some great ideas for how to identify changing data if you don’t have the budget for Enterprise Edition and really brings back memories of the my early days as a DBA before there was any built-in change tracking in SQL Server.
Andy Galbraith (blog|@DBA_ANDY) gives us T-SQL Tuesday #74 – Who Grew The Database?. Andy provides a good method for finding information about database growths from the default trace. It’s always useful to know ways to find information about changes in times when you don’t already have something set up to track it.
The next participating post came from me. In my post T-SQL Tuesday #74: Ch-ch-changes, I talk about Query Store, a new feature in SQL Server 2016, and how you can use ti to find query plans and query performance that changes over a period of time including some handy scripts I wrote for you to use.
Derik Hammer (blog|@SQLHammer) gives us a unique usage for the merge command in his post T-SQL Tuesday #74 – Be the change (MERGE static data). I have only seen one other developer use this method for deployments like this, and I thought it was odd back then. I then came to realize it was actually pretty clever. I feel better about my final opinion knowing the someone else has come up with this idea as well.
Steve Jones (blog|@way0utwest) talked about the solution they came up with for a problem on SQL Server Central in his post T-SQL Tuesday #74–The Changes. Steve’s post had a unique angle to it because it dealt in part with detecting from where changes originated and how they had to deal with that to scale out their email system for the site.
James Anderson (blog|@DatabaseAvenger) chose to tackle an angle to this topic that most people seemed to avoid like the plague in his post Managing Change Data Capture T-SQL Tuesday #74. James calls out an aspect of CDC that is generally overlooked by people who use CDC until they get burned by it. If you are considering using CDC, you should definitely give this post a read.
I want to reiterate my thanks to everyone who submitted a blog post or read one or more of the participating blog posts. I want to also call out a special thanks to Adam Machanic (blog|@AdamMachanic) who founded T-SQL Tuesday. So if you enjoy this monthly event or wish to host one yourself, be sure to drop a note of thanks and/or request to host to him.