Voice of the DBA

Category: Editorial

  • Spring Connections and Learning at PASS On Tour

    It’s just a few weeks until the spring PASS On Tour Chicago 2026. This is a smaller version of the PASS Summit that will be coming to Seattle in November and has been running for 26 years each fall. Myself and many other data professionals have found immeasurable value from the time we’ve spent with others at these events.

    Connect. Share. Learn.

    That’s the motto that PASS adopted many years ago, and I love it. We get to network with each other, talk about our experiences, challenges, and struggles, and hopefully find a way past them. We are stronger as a team, and the synergies that come from people working together allow us to accomplish more than we ever would alone.

    The PASS Summit has been an event at which this has happened, and I’ve been very lucky to attend most of them. I’ve learned lots of tips and tricks in sessions, but much more by talking with others before or after the presentations. I’ve been inspired by others and warned about walking down paths where people have struggled. All of the knowledge shared with me has helped grow my career across the last 26 years.

    In 2025 there were 3 tour events, and I was able to attend all of them. They were small, but I still had ample opportunities to connect with others, learn from them, share with them, and get out to a few dinners with friends who didn’t plan on coming to Seattle, but they made one of the regional events.

    This year there is just one tour stop in the US. May 7-8 in Chicago, and I get to go again. There’s a fantastic lineup of speakers, some great pre-cons, all at a relatively cheap price compared to many other data events. Chicago is easy to get to and it’s not too expensive to spend a few days in one of America’s classic cities.

    I hope you’ll join me in Chicago. It’s short notice, but there are still chances to join, and I’ve got a discount code if you ping me 😉

    Steve Jones

  • Local Agents

    Recently I saw an interesting article, saying that someone could build a general purpose coding agent in 131 lines of Python code. That’s a neat idea, though I’m not sure that this is better than just using Claude Code, especially as the agent still uses the online version of  the Claude model from Anthropic to generate code or perform other tasks. There’s a video in the article showing how this code can be used to perform some quick tasks on a computer.

    However, the code isn’t specific to Anthropic. It can be used with any LLM, and I started doing just that, with a copy of the code from the article, but modified to use a local AI LLM running under Ollama. You can see my repo and feel free to download and play with it. It’s expecting a local LLM on 11434.

    I’m a big fan of local agents for a variety of reasons, but mostly because I know humans tend to do dumb things. Especially with new technology, and maybe even more especially in development areas.

    That includes me.

    I’ll take shortcuts. I’ll give an agent sysadmin on a dev database to try things. I want to be able to experiment, learn, and see what works. I want to learn how to use tools and fail using them. That’s how I get better. That’s how I get better in sports, in music, and in technology.

    And that’s not a project I can take time to work on. I don’t get to dedicate time to just learn and then go back to work. Work never ends. It’s a grinding, constant, continuous treadmill of things I need to deliver to others. I have to learn to experiment around those deliverables when I can find spare moments.

    With AI, that means we’ll do things that get InfoSec teams to cringe. I get the concerns over data transiting networks and going to who-knows-where to be used who-knows-how-by-others. I appreciate business subscriptions that guarantee that data won’t be used, but I also want extra safeguards at times. That means local models. Not necessarily on my laptop, but in my data center.

    Plus, that way I (or my org) can control the costs and manage expectations.

    I hope local models and local agents catch on, I hope more vendors support them and more organizations are willing to run them. Even in something like AWS Bedrock or Azure Open AI or Vertex AI. Then I can rent the latest and greatest hardware, but have more control over how my organization uses it.

    Steve Jones

    Listen to the podcast at Libsyn, Spotify, or iTunes.

    Note, podcasts are only available for a limited time online.

  • Every Database Has Problems

    Every database platform has some strengths and weaknesses. Some more than others. I caught this site (NSFW) from Erik Darling, and it made my day. I was having a tough one when this site got me to smile and chuckle out loud a few times. I especially like the MySQL and SQL Lite links (again NSFW).

    Every platform that you might choose to use to back an application can work in many situations. Certainly scale and load are factors to consider, but for the major relational database platforms, most will work fine for many applications. Some might work better than others, but there are always tradeoffs. There are pros and cons. This is also true for the major NoSQL platforms, though most of my experience is with relational ones, so I tend to lean in that direction.

    At the same time, any platform can fail horribly.

    What’s the difference? Quality database design and software engineering. If you have a knowledgeable staff that works with the platform, they can likely make it work well. If they don’t consider the database impact when they code, or aren’t skilled with that platform, they can easily make it seem like the database doesn’t work well at all. Lots of hardware can help, but it often can’t outrun poor data models, poor query structures, or a lack of indexing.

    Quality of code matters, as many data professionals know. We often aren’t given enough time to do the job right, but we know that’s the case. It doesn’t do any good to complain or bemoan the fact that there is never enough time to fix things or improve them.

    We need to write better code to start with, which means learning to write better code. Understand what impacts performance, where you can change your patterns and habits. Watch Erik’s posts, learn from Jeff how to build test data sets to stress your queries if you don’t have good test data. Learn to do a better job in the same amount of time.

    Changing platforms won’t magically fix things, no matter what your CTO/director/manager thinks. Especially if your team doesn’t already have experience on the new platform.

    Steve Jones

    Listen to the podcast at Libsyn, Spotify, or iTunes.

    Note, podcasts are only available for a limited time online.

  • The New OS Wars

    In the last year I’ve seen a lot of statements about data and sovereignty between countries. While there have been concerns in the past, there seems to be more worry around the world with AI services primarily being run by, and hosted by, US companies. Plenty of my customers at Redgate Software have concerns over our ability to see data when we run AI models, though we don’t store the data. Once the session ends, the data is discarded by policy

    Recently I saw a piece about France trying to rid itself of the reliance on US technology, specifically the Windows OS from Microsoft. They are looking to move to their own version of Linux, as well as a number of open source software packages. This quote was fascinating to me: “We can no longer accept that our data, our infrastructure, and our strategic decisions depend on solutions whose rules, pricing, evolution, and risks we do not control.”

    With AI being added to lots of software, including OSes, I suspect that other countries might look to follow France. I know the EU is looking to move, and Brazil has been trying to use more Linux and OSS for decades. While I find Windows works well, I completely understand wanting to move, especially in this era where many software packages are web-based and can run on a different OS.

    SQL Server runs on Linux, and half of my testing is on Linux, since I run SQL Server in a container on my laptop. My desktop still has a native Windows install, but I find it easy to port almost all code back and forth between the two versions. While I understand others might have a preference for PostgreSQL or MySQL or some other OSS platform, I think SQL Server provides a great value for many organizations. I also think it’s incredibly hard to port your software and data from one database platform to another.

    I do wonder if governments or organizations outside the US that look to leave Windows will also look to leave SQL Server. It’s one thing to move away from the OS and software like Office. A little training will get most users productive on a new system in a relatively short time. Moving a software application and its database is a much larger challenge.

    I expect SQL Server to remain incredibly popular for many years, and with the ability to configure the new AI capabilities to use your own models, I am not sure a country that wants to reduce their reliance on US technology will choose to do so for their databases. They will likely start elsewhere and continue to use SQL Server for years.

    Steve Jones

    Listen to the podcast at Libsyn, Spotify, or iTunes.

    Note, podcasts are only available for a limited time online.