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Day: August 7, 2026

Spatial Data in MySQL vs PostgreSQL

Published 2026-08-07 by Kevin Feasel

Aisha Bukar contrasts two data platforms:

MySQL and PostgreSQL both store spatial and geometric data, but they take fundamentally different approaches. While MySQL bakes spatial support directly into its engine, PostgreSQL separates two ecosystems: native geometric types (built-in, flat-plane, non-geographic), and PostGIS (a full GIS extension with coordinate systems, projections, and hundreds of spatial functions).

For most real-world location-aware applications — GPS tracking, geofencing, distance queries — PostGIS is the more powerful option, though MySQL 8.0 closed the gap considerably for common use cases. This guide compares their architectures, data types, indexing strategies, spatial functions, and what to watch out for if you’re migrating between them.

Click through for the comparison.

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Issues with INSERT-EXEC

Published 2026-08-07 by Kevin Feasel

Erik Darling has two problems:

All right. So, the first thing I’m going to show you is the blocking problems that Insert Exec can incur. And the reason…

why this happens is because when you use insert exec, the exec portion of the insert has a transaction opened around it. So if your exec is doing more, is like say executing a store procedure that does a bunch of stuff which might include taking locks on things, might include executing other store procedures that perhaps take locks on things, those locks will be held until the insert completes. That can be a very very shocking experience for a lot of people.

Click through to learn more about both problems, including windows of time when SQL Server gets blackout drunk and can’t account for its time.

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Implementing the Gauss Kronod Quadrature Formula in SQL Server

Published 2026-08-07 by Kevin Feasel

Sebastiao Pereira implements a formula:

Gauss-Kronrod quadrature is a numerical integration method that extends the Gaussian quadrature providing high accuracy and a built-in error estimation. It is based on the work of Carl Friedrich Gauss and Alexander Kronrod. The Kronrod method reuses all Gauss nodes adding extra points obtaining one integral estimate for Gauss and another for Kronrod and the differences gives the estimated error.

Click through to see how you can do this in T-SQL.

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Datatypes and Constraints in Microsoft Fabric Data Warehouses

Published 2026-08-07 by Kevin Feasel

Louis Davidson starts digging in:

There are three major “engines” in Fabric that I have seen that use T-SQL. There is the SQL Azure Fabric engine, the Lakehouse, and the Data Warehouse. Having this capability to manipulate data is wonderful, but there are some things you need to understand before you start writing code (unless you want to learn them the hard way like I have. I also will not profess to have found all of these differences. Changing my mindset when using these engines was the subject of this editorial

Read on for some inconsistency.

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Simplifying Code via Computed Columns

Published 2026-08-07 by Kevin Feasel

Andy Brownsword moves an expression:

Computed columns allow us to bake logic into our schema. I find particular use for these when reviewing or optimising established solutions where you spot the quirky ways the data is being used.

Here I want to demonstrate 3 symptoms and show how different implementations of computed columns solve them.

Click through for the technique. It certainly won’t solve every performance problem relating to non-SARGable functions, but it does work pretty well on specific classes where you have limited control over the code.

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Working with Blob Leases

Published 2026-08-07 by Kevin Feasel

Miles Cole explains how leasing works with Blob Storage and Data Lake Storage blobs:

Leased a blob? No, this isn’t some new car model with a great leasing offer. Blobs are files in ADLS / OneLake, and leasing is the process of temporarily holding an exclusive lock on one of those files. Does this sound useful in data engineering? Maybe not at first, but in this post I’ll show why understanding the extended features of object storage APIs like blob leases can be invaluable when building data systems that scale.

I’ve never actually done this, but it’s a smart way of preventing multiple job agents from picking up the same work.

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