Contributing to Community

This post is a response to this month’s T-SQL Tuesday #102 prompt by Riley Major. T-SQL Tuesday is a way for SQL Server users to share ideas about different database and professional topics every month.

The prompt I’ve chosen to write about this month is how and why I got started contributing to the SQL Server community.


About a year ago, I was determined to improve my presentation skills.  I knew that in order to do that I needed to get more practice speaking.

I already was at my max for presenting at local user groups, conferences, etc… because at some point it becomes too cost and time prohibitive to travel to more events.  As an alternative, I decided that if I couldn’t get more practice by speaking in person, I could at least film myself presenting.

And I figured if I’m already filming myself presenting, I might as well put a little extra polish on it and make the content available for others to watch.

And that is how I started filming weekly videos about SQL Server.

SQL Server Videos

There are already plenty of great SQL Server presentations on YouTube, spanning a plethora of topics from a variety of experts who know way more about SQL Server than me.

Whenever I want to learn about a SQL Server topic, I search for something like “SQL Server backups” or “SQL Server columnstore indexes” on YouTube.  There are plenty of great recorded presentations, virtual chapter screencasts, Q&As, and other tutorials for learning almost any topic you can imagine.

However, sometimes I’m not in the mood to watch in-depth hour long presentations.  Sometimes I want to watch a short, informative, regularly scheduled entertaining SQL videos – and this is where I saw a gap in programming.

So what better way to get what you want than by scratching your own itch.  I figured if I want to watch that type of SQL Server video, then I’m sure other people out there want to watch those same kinds of short SQL videos too.

Bert, the Director

When I was a kid, I wanted to be a movie maker.  In particular, I was entranced by special effects, so I made movies with friends that involved plenty of lightsabers, explosions, and green screen effects all throughout middle school and high school.

So while making SQL videos wasn’t going to be totally new territory, I sure was unprepared for all of the initial work involved.

For the first three months, I was spending 15-20 hours per week writing, creating demos, shooting, editing, publishing, and marketing my videos.  Over time I’ve cut this process down to 8-10 hours a week, a more manageable amount of work that I can mostly get done on weekend mornings before the rest of the house wakes up.

Results

Making videos about SQL Server has been an amazing experience.  Not only do I personally feel fulfilled creating something week after week that improves my own skills, but it’s rewarding to receive positive feedback via comments, messages, and emails that I’m also helping others become better SQL developers.

Contributing has also made me appreciate how amazing the #sqlfamily community truly is.  Everyone I talk to is wonderful and supportive, and everyone I meet wants to see one another succeed.

Your Turn

If you aren’t already, I hope you consider contributing to the community .  Whether it be via blog posts, code contributions, presenting, tweeting, or making videos, giving back to the SQL Server community will grow your own skills and allow you to meet some really great people.

It can be scary putting yourself out there publicly, but don’t let that stop you.  If you give it your best then the SQL Server community won’t let you down.

Thanks for reading. You might also enjoy following me on Twitter.

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3 Essential Tools For The SQL Server Developer

This post is a response to this month’s T-SQL Tuesday #101 prompt by Jens Vestergaard. T-SQL Tuesday is a way for SQL Server bloggers to share ideas about different database and professional topics every month.

This month’s topic is about what essential SQL Server related tools you use on a regular basis.


SQL Server Management Studio is an excellent tool for my day to day SQL Server developing needs.

However, sometimes I need to do things besides writing queries and managing server objects.  Below is a list of my three most used tools I use on a regular basis when working with SQL Server.

Watch this week’s episode on YouTube.

1. WinMerge

Often I need to compare the bodies of two stored procedures, table definitions, etc… to find differences.

While there are some built-in tools for doing difference comparisons in Visual Studio and SSMS source control plugins, I prefer using the third-party open-source tool WinMerge:

The tool is a pretty straightforward difference checking tool, highlighting lines where the data between two files is different.

It has some other merge functions available in it, but honestly I keep it simple and use it to just look for differences between two pieces of text.

2. OnTopReplica

When on a single display, screen real estate is at a premium.  This is especially true if you are forced to use a projector that’s limited to 1024×768 resolution…

OnTopReplica to the rescue!  This nifty open-source tool allows you to select a window and keep it open on top of all other windows.

This is great for when I want to reference some piece of code or text on screen while working in another window:

In addition to forcing a window open to stay on top, it allows you to crop and resize that window so only the relevant parts are visible.

The OnTopReplica view is live too – that means it’s great to use as a magnifier on your SSMS result sets when presenting (instead of constantly having to zoom in and out with ZoomIt):

Look at those beautifully zoomed in results!

3. ScreenToGif

Sometimes explaining concepts with pictures is hard.  For example, wouldn’t that last screenshot be way better if it was animated?

ScreenToGif is an open-source screen capture tool that does an excellent job compressing your recorded videos into gif animations.  It also allows editing individual frames, allowing the addition of text, graphics, and keyboard shortcuts.

Thanks for reading. You might also enjoy following me on Twitter.

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Full Automatic Tuning: SQL Server 2026’s Most Killer Feature

This post is a response to this month’s T-SQL Tuesday #100 prompt by the creator of T-SQL Tuesday himself, Adam Machanic.   T-SQL Tuesday is a way for SQL Server bloggers to share ideas about a different database or professional topic every month.

This month I’m going down the science fiction route and pretending that I’m writing about a new SQL Server feature in 2026.


Fully Automatic Tuning

I was really excited when automatic tuning capabilities were first introduced in SQL Server 2017.  I couldn’t wait to say so-long to the days where I had to spend time fixing basic, repetitive query tuning problems.

And while those first versions of automatic plan choice corrections were fine, there was a lot left to be desired…

Fortunately, Microsoft has fully leveraged its built-in R and Python services to allow for advanced automatic tuning to make the life of SQL Server DBAs and developers that much easier.

On By Default

Perhaps the coolest part of these new automatic tuning capabilities is that they are on by default.  What this means is that databases will seem to perform better right out of the box without any kind of intervention.

I think the fact that Microsoft is confident enough to enable this by default in the on-premise version of SQL Server shows how confident they are in the capabilities of these features.

Optimize For Memory and Data Skew

While the first iterations of automatic query tuning involved swapping out query plans when SQL Server found a regression in CPU performance, the new automatic plan correction is able to factor in many more elements.

For example, instead of optimizing for CPU usage, setting the new flag  OPTIMIZE_FOR_MEMORY = ON  allows SQL server to minimize memory usage instead.

Also, with the addition of the new  “Optimized” cardinality estimator (so now we have “Legacy”, “New”, and “Optimized” –  who’s in charge of naming these things???) SQL Server is able to swap out different estimators at the query level in order to generate better execution plans!

What time is it?

Another new addition to automatic plan corrections is SQL Server’s ability to choose an appropriate execution plan based on historical time-of-day server usage.

So if a query is executing during a lull period on the server, SQL Server is intelligent enough to realize this and choose a plan that is more resource intensive.  This means faster query executions at the cost of a more intensive plan – but that’s OK since the server isn’t being fully utilized during those times anyway.

Making use of hardware sensors

As the world continues to include more data collecting sensors everywhere, SQL Server makes good use of these data points in 2026.

Tying into the server’s CPU and motherboard temperature sensors, SQL Server is able to negotiate with the OS and hardware to allow for dynamic CPU overclocking based on server demands.

While this option is not turned on by default, enabling dynamic overclocking allows for SQL Server to give itself a CPU processing boost when necessary, and then dial back down to more stable levels once finished.

This obviously won’t be a feature used by everybody, but users who are willing to trade off some stability for additional analytical processing performance will love this feature.

How I Stopped Worrying And Learned To Love Automatic Tuning

At the end of the day, we are our own worst enemies.  Even with the latest and greatest AI technology, we are capable of writing queries so terrible that even the smartest machine learning algorithms can’t grasp.

While SQL Server’s automatic tuning features work wonderfully on the boring and mundane performance problems, there are still plenty of performance problems that it leaves for us to troubleshoot.

And I love that.  Let the software optimize itself and maintain a “good enough” baseline while letting me play with the really fun performance problems.

I’m sure these features will continue to evolve – but so will we, working on new problems and facing new data challenges.

Thanks for reading. You might also enjoy following me on Twitter.

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