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Category: Administration

A Primer on Database States

Jeff Iannucci lays out the list:

I’ve recently been asked by some folks about different states for SQL Server databases. Questions like “what’s the state of a database with log shipping?”,  “can I fix a database in (whatever) state with a restart?”,  and “which is the bad one, RECOVERY or RECOVERY PENDING?”

Hopefully you don’t have to try to figure out if your database is in a bad way or not because of an unusual state, but I presume when you do you will need to know as soon as possible. So, I’ve put this handy list of possible database states together to help you in your moment of need.

Click through for the full set.

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SQL Login Overhead in SQL Server 2025

Sean Gallardy has a wonderful rant:

There were a few emails about login times so I figured it warranted a blog post. Strap in, this one goes sideways fast.

Some people noted that the amount of time to log in with a SQL Login in SQL Server 2025 all of a sudden took longer. This is clearly stated in the Docs, though the way it is written is documented is problematic.

As Sean mentions, this is on purpose and it is good. Yeah, the amount of time it takes to log in using SQL authenticated accounts in SQL Server 2025 is higher. That’s because the mechanism to log in is now considerably more secure than it was before. And let’s be honest: how frequently are you logging into SQL Server? What percentage of your processing time does that take? Because if the answer is “a large percentage,” that sounds like a job for connection pooling or revising the calling application.

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Performing a Lakehouse Table Health Check

Jon Lunn looks at a stored procedure:

Microsoft have rolled out a new ‘sys’ stored procedure called ‘sys.sp_get_table_health_metrics’ for checking the health of your tables in your Lakehouse. And it outputs a lot of metrics looking at the state of your table and anomaly detection in them.

What does it check for?

Click through for that answer, as well as some of the things you should watch for in the procedure results, and what you can do if it does catch something.

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Monitoring the Refresh of a Semantic Model

Reitse Eskens checks the logs:

As you’ve probably heard and read before, monitoring your Fabric environment as a whole is quite important. It really does help to know what’s going on.
Now, one thing I’ve learned over all these years is that report users do quite like their data to be as fresh and up to date as possible. And, when the data seems stale, they tend to ask questions.

Read on for some notes covering how to refresh a semantic model, when you might want to, how to automate it, and how to monitor the refresh process.

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Ghost Records in SQL Server

Martyn Jones sees dead records:

When a delete operation is executed, or when an update causes a page split, a marker is set in the page header, and each row is marked to show that the record is to be deleted; this is the process of creating ghost records. The concept is to improve performance as the data is not immediately removed, and, with row-level locking, it helps minimise blocking and supports efficient concurrency under typical isolation levels such as Read Committed and above. If a transaction is later rolled back, the cost of effectively restoring the row is considerably reduced as the data doesn’t need to be reinserted, only the marker removed. Later demos will show this in action.

This is the first part of a longer series on ghost records and ghost cleanup.

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Building a Lakehouse Table Health Pipeline

Gilbert Quevauvilliers builds a pipeline:

In this post I will show how I used GitHub Copilot CLI / Agent mode in VS Code to create a Microsoft Fabric pipeline that checks Lakehouse table health and only optimizes tables that require maintenance. I’ll also show the prompts I used, the issues I ran into, and how Copilot helped me resolve them.

Recently Microsoft announced Lakehouse table health. The post showed how you can check can check the health of your Lakehouse table in a very simple way.

Read on to see what this feature can do, as well as how Gilbert was able to gin up (with the help of GitHub Copilot) a pipeline to optimize lakehouse tables. What I appreciate is that Gilbert also included the errors in the process, rather than making it seem like everything with perfectly the first time around.

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SSMS Tools in VS Code

Denny Cherry has a new VS Code extension:

Are you a user of VS Code, but you wish that the MSSQL extension had more of the SQL Server Management Studio features? Good news, there’s now a VS Code Plugin that gives you those capabilities in VS Code by using the “SSMS Tools for SQL Server” extension.

Click through to see what it includes. There’s a pretty decent amount of existing SSMS functionality in this extension, especially on the database administrator side, where Azure Data Studio and VSCode historically have not focused.

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Too Many Tables and PostgreSQL

Laurenz Albe uncovers an oddity:

Recently, I helped a customer investigate database problems. It turned out that these problems could be traced back to too many tables in the database. Since this may come as a surprise to many users, I thought it worth the while to write about it.

Click through to see what was happening, as well as a demonstration of the problem. Granted, when you start talking about tens of thousands of tables, something has gone catastrophically wrong in your database architecture.

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Master Database Compatibility Level

Jeff Iannucci explains an issue:

We were attempting to install a troubleshooting stored procedure in the master database of a SQL Server 2016 instance when we received the following error.

Msg 195, Level 15, State 10, Procedure sp_ShootTheTrouble, Line 227 [Batch Start Line 7]

‘TRY_CONVERT’ is not a recognized built-in function name.

This was unexpected, as TRY_CONVERT has been a command since SQL Server 2012. As a consequence, we were unable to install the stored procedure.

Tracking system database compatibility levels is a minor chore but an important one after an upgrade.

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