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Curated SQL Posts

SQL Server Error Log Tips

Published 2025-07-07 by Kevin Feasel

Kevin Hill notes that the error log isn’t just for errors:

SQL Server’s Error Logs often get overlooked, until something breaks. But if you know how to use them, they can tell you what went wrong before you’re knee-deep in outage mode.

Whether you’re a sysadmin who inherited SQL or an MSP juggling multiple environments, understanding the ErrorLog is low effort, high return.

Let’s decode the basics.

Click through for examples of information you can find in the error log. Kevin mentions cycling the error log weekly. Back in my DBA days, I’d cycle them daily because I didn’t want the files to grow too large and become unwieldy. Some of this, of course, depends upon how hard people are pushing that box and how much you need to log.

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Backup and Restoration via pgbackrest

Published 2025-07-07 by Kevin Feasel

Warda Bibi sets up a backup management system:

Recently, we worked with a client who was manually backing up their 800GB PostgreSQL database using pg_dump, which was growing rapidly and had backups stored on the same server as the database itself. This setup had several critical issues:

  • Single point of failure: If the server failed, both the database and its backups would be lost.
  • No point-in-time recovery: Accidental data deletion couldn’t be undone.
  • Performance bottlenecks: Backups consumed local storage, impacting database performance.

Read on to see how pgbackrest can address each of these concerns.

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Using a File Cache in SSIS

Published 2025-07-07 by Kevin Feasel

Andy Brownsword makes those SSIS jobs run faster:

Last week we looked at using a cache to improve lookup performance. We saw how a cache improves performance by being able to reuse reference data repeatedly. That used a regular cache but it’s not the only option available to us.

In this post we’re going to look at the File Cache option which can achieve the same results – plus a little more.

My experience with file caches is that they’re a bit finicky but when you get them running, they can provide a significant speed-up to data enrichment tasks.

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Wait Stats in Oracle vs PostgreSQL

Published 2025-07-03 by Kevin Feasel

Kellyn Gorman continues a series on PostgreSQL for the Oracle DBA:

As discussed in an earlier blog post, Oracle groups wait events into wait classes like User I/O, System I/O, Concurrency, Network, Idle, Commit, and more.  By grouping wait events into categories, it helps the technologist identify where time is being spent in the database, (DB Time) and as there is often a correlation between waits, identify culprits.

Read on to see how the two systems compare.

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What’s New in SQL Server 2025 CTP 2.1

Published 2025-07-03 by Kevin Feasel

Brent Ozar looks under the covers:

When CTP 2.0 came out, I blogged the thousands of new feature flags, messages, and system objects in SQL Server 2025 CTP 2.0, and I haven’t had the time to dig more deeply into those yet. In that post, I discussed the new sys.dm_feature_switches table, and I mentioned that it might disappear before release. Indeed it has – last week’s new CTP 2.1 removed access to that table, meaning that was probably our one-time shot to get a glimpse into something cool and undocumented. I would have loved to have been a fly on the wall when folks at Microsoft read my blog post and realized they’d left that table unguarded and publicly visible, hahaha. I love my job.

So now CTP 2.1 is out, and it comes with a few things I think you’re going to be interested in.

Read on to see what Brent has found.

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Thirteen Power Query Tips

Published 2025-07-03 by Kevin Feasel

John Kerski has a baker’s dozen:

When I first started with Power Query, it was in Excel, through the Power Pivot feature. I was amazed at how I could transform data with just a few clicks and quickly create PivotTables. Then, when Power Query appeared in Power BI, I began working with larger data sources and more complex projects.

Through many trials and tribulations, I learned the capabilities of Power Query and the M language (the functional language that actually transforms our data), as well as its idiosyncrasies. Unsurprisingly, with Power BI adoption and rapid growth, many newcomers are learning the same lessons I did.

Read on for some of John’s early pain points. By the way, regarding John’s banker’s rounding note, that’s the norm for .NET, though not for Excel or SQL. It’s also more accurate in the aggregate than “to the 5’s” rounding, though it can be confusing to people who aren’t expecting it.

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High Availability Architecture for PostgreSQL

Published 2025-07-03 by Kevin Feasel

Umair Shahid adds a 9:

Most teams building production applications understand that “uptime” matters. I am writing this blog to demonstrate how much difference an extra 0.09% makes.

At 99.9% availability, your system can be down for over 43 minutes every month. At 99.99%, that window drops to just over 4 minutes. If your product is critical to business operations, customer workflows, or revenue generation, those 39 extra minutes of downtime each month can be the difference between trust and churn.

Click through for some of the tools and practices that can help get you there in PostgreSQL.

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Month-over-Month and Year-over-Year Calculations in Power BI

Published 2025-07-03 by Kevin Feasel

Boniface Muchendu does a bit of comparison:

Power BI variance measures are essential for delivering actionable insights through dynamic comparisons like month-over-month (MoM) and year-over-year (YoY) performance. This guide shows how to build flexible, filter-aware DAX measures and apply them within clean, user-friendly visuals to enhance your reports.

Click through to see them in action.

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SQL Agent Job Logging Outputs

Published 2025-07-02 by Kevin Feasel

Eitan Blumin shares some recommendations:

In many SQL Server environments, DBAs configure SQL Agent jobs with retry attempts (which is a smart move to handle transient issues gracefully). But with it comes a hidden pitfall that often goes unnoticed:

Retry-enabled job steps can silently overwrite logs or cause runaway log growth, depending on how the output file is configured.

The culprit? Improper use of append settings and missing time-based tokens in output file paths.

Read on to learn more.

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