A Fine Slice Of SQL Server
Greg Low breaks down a document:
If you’ve started to work with vector databases and looked at using text embeddings for AI search, you might have come across the term chunking and wondered what it relates to. In this article, I’ll explain the concept in general – and then show how it works in SQL Server 2025.
Read on for that explanation. Greg also includes a quick example of how this looks in SQL Server 2025 when passing text data through an embedding model.
Leave a CommentLukas Eder covers an esoteric bit of syntax:
Some SQL operators are as esoteric as they’re powerful. One of the oldest operator that you’ve likely hardly ever used in real world applications is
NATURAL JOINwhich is the default in relational algebra. We’ve covered a funky use-case forNATURAL JOINearlier on this blog.
Click through for a similar example using JOIN USING. It’s best to be specific in your SQL queries, at least the permanent ones that you add to scripts you expect to re-run in the future or make part of applications.
Marco Russo and Alberto Ferrari provide a deeper answer:
A very common request by Power BI newbies is, “How can I use a slicer to filter a measure rather than a regular model column?” The most common answer to this question is, “You cannot filter a measure through a slicer”. The answer is entirely correct because there is no such thing as “filtering a measure”. However, elaborating on the why gives us a good way to explain not only what is wrong with the question, but also how to further reason about the requirements needed to obtain a working solution.
This blog post is an example of how challenging it can be to answer a beginner’s question, where the immediate answer is “No, you can’t do that” but the underlying problem is solvable.
Leave a CommentRich Benner hires some movers:
As consultants, we often see system databases existing on the C drive on SQL Servers. There are some issues with this setup, and the biggest is: if one of your system databases grows and fills your C drive, you will likely crash the OS. If that happens, we’re in big trouble. Therefore, moving system databases becomes a necessary operation at times.
This is such a common issue because the default locations are set to C for these databases and that’s where they end up on fresh installs 99% of the time. Don’t worry! If you’re in this situation you’re not alone.
Click through for a query that shows which databases are on which drive and how to migrate databases post-install.
Leave a CommentRichard Yen explains why it’s not the best tool for the job:
At small scale, using Postgres as a job queue is totally fine, and I’d even say it’s the right call. Fewer moving parts, one less system to manage, ACID guarantees on your jobs. What’s not to love?
The problem is that “small scale” has a ceiling, and the ceiling is lower than most people expect. When you’ve got thousands of concurrent workers hammering a jobs table with
SELECT ... FOR UPDATE SKIP LOCKED, things start to behave in ways that aren’t obvious from the application layer. CPU usage creeps up. Also vacuum sometimes can’t keep up. Finally, in the wait event stats, you start seeing ominous entries likeLWLock:MultiXactSLRUstacking up across many backends.This pattern has tripped up teams more than a few times, and it usually plays out the same way: everything works fine in dev and staging, then goes off a cliff in production once the concurrency gets real. So let’s dig into why this happens, and what the alternatives look like.
Click through for more information. It’s the same on the SQL Server side of the house: once you hit a concurrency threshold, performance drops off of a cliff.
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