Learning – Curated SQL

Guidance on Building an Application

Published 2026-05-01 by Kevin Feasel

I do absolutely consult for software vendors. I used to work for Quest Software, and I’ve consulted for Amazon, Google, and a lot of third party software vendors. It’s real work that requires real effort on my part, and I need to get paid for that.

Having said that, I still wanna help you for free, so I’ve put together this blog post with my favorite advice for software makers. There’s a lot of hard-learned lessons in here, and I hope you can just read ’em and avoid some of the most common pitfalls that folks run into.

As one of the few people in the SQL Server community who’s good at marketing, Brent’s advice is worth a careful read.

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The State of the Database Market

Published 2026-04-30 by Kevin Feasel

Simple Talk’s editor digs into the data:

Leading research and analysis firm Gartner recently revealed its DBMS Market Share Ranks for the 2011-2025 period, and it shows a clear pattern. That is: while the dominant database vendors are losing their stranglehold on the market, it’s happening very slowly – so don’t expect to see big changes at the top any time soon.

It’s a trend already uncovered in the Redgate DB-Engines rankings in recent times, despite it using a very different set of metrics compared to Gartner’s analysis.

I had no idea that Redgate owned DB-Engines. But there’s some interesting information to come out of these results, especially because they come at the problem from very different angles.

T-SQL Tuesday 197 Round-Up

Published 2026-04-20 by Kevin Feasel

Steve Hughes learns something new:

Thanks to everyone who joined the blog party this month. I noticed three themes in the responses. Every response had one or more of these themes woven into their response.

I learned something.

I discovered ways to improve my presentations.

I get more value in the hallway conversations.

Click through for this month’s participants and what they’ve learned.

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Presenting for Impact

Published 2026-04-14 by Kevin Feasel

Rob Farley tells a story:

I like this topic from the legendary Steve Hughes. It’s been a long time since I’ve seen him, but he was always a thoroughly good guy. We both spoke at conferences back in the heyday of the SQL community, and although his journey has been tougher than most in recent years, he is still impacting the world in amazing ways.

Steve is hosting this month’s T-SQL Tuesday, and asks about what we’ve learned from conference sessions, things which impacted us and how we work. It’s an interesting topic for two reasons – firstly, I enjoy giving conference presentations, and secondly, they’re really not my preferred way of learning.

Rob goes on to talk about conference sessions that caught his interest. One book that helped me considerably in my ability to present is Peter Cohan’s Great Demo! This is, admittedly, for sales presentations rather than technical presentations. However, I think it’s pretty straightforward to map most of the concepts to technical demos, and the advice in the book is great for getting your point across early and letting people make sure they are in the right room at the right time straight from the get-go.

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Disclosing Testing Machines

Published 2026-03-13 by Kevin Feasel

Louis Davidson lays out an argument:

Something that every writer needs to be careful of is doing too much benchmarking-type work. In many of the software licensing agreements you have signed, you promise not to do that. But at the same time, you can generally give out performance numbers if you aren’t making claims about particular software, especially compared to another.

So, if you come up with an algorithm to do something in a better way than you have seen, it is nice to show the software, give the reader access to the code you are showing the performance of, and include the computer you are running it on.

Louis is referring to the DeWitt Clause, a fairly common clause in commercial database products that came about because Oracle was angry that David DeWitt made them look bad by providing a fair comparison to other platforms.

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Where the Buck Stops

Published 2026-03-06 by Kevin Feasel

Louis Davidson talks slop:

I loathe the phrase AI Slop. I have said it before, I don’t like the phrase because it is generally attributed to some content that a person has posted. I blame the poster, not the generator. We all use AI these days, just like they used tractors to farm, computers to do accounting work, and CGI to produce movies. These are all tools.

But when I sign my name to something, it is really and truly mine. In this blog, I will discuss this and more. So as the title says, don’t blame AI, Google, a person’s teachers in grade school, nope. Blame the person who said, “This is good enough to put out in my name”, or in other words, the person in the byline. For this post and video, that is Louis Davidson.

I understand where Louis is going with this and it’s fair. When you publish something, the person ultimately responsible looks suspiciously like the picture on your driver’s license. But I think it can serve as a useful descriptive term for a category of garbage output without removing agency from the perpetrator.

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Bluebox: An Evolving Sample Database for PostgreSQL

Published 2026-02-16 by Kevin Feasel

Ryan Booz has a sample database:

Sure, there are datasets everywhere. Kaggle currently lists over 600,000 public datasets, but most of them are static CSV files that you load once and never touch again. Great for a one-time analysis, not so great for learning how a real database behaves over time. The Postgres Wiki lists a few dozen sample databases, too. And shoot, your shiny new AI coding buddy can help you create one if you want to put the time in.

The problem with most of these datasets is that they’re primarily static. If you’re lucky, some of the datasets might produce new data dumps once a month to keep things “current”. But the problem is that you can’t really practice query tuning if your data never changes. You can’t explore vacuum behavior when there are no updates. You can’t test monitoring tools when nothing is happening.

Click through for more information on Bluebox, as well as a Docker container containing several helpful tools and processes to make this data evolve over time.

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T-SQL Tuesday 194 Round-Up

Published 2026-01-28 by Kevin Feasel

Louis Davidson has made a big mistake:

As I sit here, preparing to write my roundup post, I have not read anyone else’s post yet. I thought it would be good to introduce the idea first, recap to the other posts, then mine. I won’t share any detail of the mistake I shared, but I do want to mention something I included in my post. Types of mistakes. Mistakes of choice, and mistakes of accidents.

Read on for a nice round-up of a popular topic.

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A Primer on Cognitive Perception

Published 2026-01-23 by Kevin Feasel

Paul Turley thinks about how we think:

You can be the greatest report designer on the planet, but if your report doesn’t meet the needs of the report consumer, it’s all for nothing. In this section, I break down the most important considerations for identifying your audience and their information needs. These are all factors to consider before you jump in and start designing your report.

Paul hits on quite a few of the foundational concepts around how humans visual stimuli and tells some interesting stories along the way.

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Tips for Teaching Technical Topics

Published 2026-01-23 by Kevin Feasel

John Deardurff shares some advice:

After 25 years as a Microsoft Certified Trainer (MCT), one thing I have learned is that teaching technical content requires more than just subject‑matter expertise. Great technical instructors create an environment where learners feel comfortable, engaged, and motivated to explore complex concepts at their own pace.

Click through for ten such tips. I tend to follow seven of them pretty well, though the three around questions are where I’m weakest.

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Category: Learning