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Author: Kevin Feasel

Tracking Memory Consumption in Fabric SQL Database

Published 2025-10-02 by Kevin Feasel

Lance Wright tracks memory utilization:

SQL Database in Fabric continues its commitment to providing you with robust tools for database management, performance monitoring, and optimization. Earlier this year, we released a performance dashboard to help you monitor and improve the performance of your SQL Database in Fabric. We’ve improved upon those performance monitoring capabilities with the ability to track memory consumption. This new capability delivers real-time, actionable data regarding the memory utilization of all database queries to help you make more informed decisions and manage SQL Database resources more efficiently.

Read on to see what you can do with this.

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VARCHAR or NVARCHAR

Published 2025-10-02 by Kevin Feasel

Brent Ozar asks a question:

You’re building a new table or adding a column, and you wanna know which datatype to use: VARCHAR or NVARCHAR?

If you need to store Unicode data, the choice is made for you: NVARCHAR says it’s gonna be me.

But if you’re not sure, maybe you think, “I should use VARCHAR because it takes half the storage space.” I know I certainly felt that way, but a ton of commenters called me out on it when I posted an Office Hours answer about how I default to VARCHAR. One developer after another told me I was wrong, and that in 2025, it’s time to default to NVARCHAR instead. Let’s run an experiment!

This is going back a long way (June of 2020) but one of my earliest YouTube videos is entitled NVARCHAR Everywhere. I’ve gotten a lot better at presentation skill since then (and have a much nicer camera), but I still stand by the arguments.

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Narrowing down Slowdown Causes in SQL Server

Published 2025-10-02 by Kevin Feasel

Kevin Hill continues a series on solving the age-old “The server is slow!” problem:

At this point you’ve:

  • Defined what “slow” means and built a timeline (Part 1).
  • Checked things outside SQL Server like network, storage, and VM noise (Part 2).

Now it’s time to open the hood on SQL Server itself.

I think Kevin’s checklist is a pretty solid one for the type of client he often deals with: one without an in-house DBA or the expertise to stay on top of server problems.

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Row Expansion in T-SQL

Published 2025-10-02 by Kevin Feasel

Louis Davidson solves a problem:

On LinkedIn a few days ago, there was a question that I found interesting about what was purported to be an interview question. The gist was “say you have a set that looks like this:

OrderId Item Quantity
------- ---- ---------
O1      A1   5
O2      A2   1
O3      A3   3

and you need to expand it to be one row based on the value in Quantity

Admittedly, this kind of problem is fairly uncommon in the business world, though this is exactly the sort of thing that a tally table can solve, and that’s what Louis uses to solve the problem. Louis also gets brownie points for praising CROSS APPLY along with tally tables.

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Scaling Kafka Streams Applications

Published 2025-10-01 by Kevin Feasel

The Confluent employee mines have a new article:

As the adoption of real-time data processing accelerates, the ability to scale stream processing applications to handle high-volume traffic is paramount. Apache Kafka®, the de facto standard for distributed event streaming, provides a powerful and scalable library in Kafka Streams for building such applications. 

Scaling a Kafka Streams application effectively involves a multi-faceted approach that encompasses architectural design, configuration tuning, and diligent monitoring. This guide will walk you through the essential strategies and best practices to ensure your Kafka Streams applications can gracefully handle massive throughput.

The post gets into some details around the kinds of limits you’ll hit during scaling, scale-up versus scale-out, and configuration settings to help with that scale.

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Tag-Based Masking in Snowflake

Published 2025-10-01 by Kevin Feasel

Kevin Wilkie gets tagging:

If you’ve followed our site for a while, you would have seen in a previous post how powerful tag-based masking policies are in Snowflake. They let you enforce consistent data masking rules across columns without constantly rewriting logic. But Snowflake hasn’t stopped there—recent enhancements now make it even easier to classify, tag, and mask data at scale. In this post, we’ll recap the essentials of tag-based masking, highlight the new functionality, and share some practical tips for rolling it out in your environment.

Kevin has a new blog theme and everything.

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Use Cases for Window Functions

Published 2025-10-01 by Kevin Feasel

I have a new video:

In this video, I take you through a variety of use cases for window functions, showing how you can solve common (and sometimes uncommon) business problems efficiently and effectively.

This video builds off of the prior two videos. Those prior two videos showed what the different window functions are and how they work. This one focuses primarily on solving business problems in sometimes-clever ways.

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Set MAXDOP in Azure SQL DB

Published 2025-10-01 by Kevin Feasel

Brent Ozar has a public service announcement:

In Azure SQL DB, you set max degrees of parallelism at the database level. You right-click on the database, go into properties, and set the MAXDOP number.

I say “you” because it really is “you” – this is on you, bucko. Microsoft’s magical self-tuning database doesn’t do this for you.

And where this backfires, badly, is that Azure SQL DB has much, much lower caps on the maximum number of worker threads your database can consume before it gets cut off. 

Click through to see what kind of error message you get and just how low these limits are.

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Adding a Drillthrough Button in Power BI

Published 2025-10-01 by Kevin Feasel

Elena Drakulevska adds a button:

If you’ve been building Power BI reports, you probably know about drillthrough.

In short: drillthrough lets users move from a summary view to a detail page focused on one data point. For example, you can right-click on Austria in a sales chart and jump straight to a page showing visuals and metrics only about Austria.

Sounds powerful, right?

The catch: most users don’t even know it’s been implemented.

The other catch: those of us sad souls using Power BI Report Server don’t get drillthrough at all.

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Finding Rows with Errors in Power Query

Published 2025-10-01 by Kevin Feasel

Gilbert Quevauvilliers goes around looking for trouble:

In the past when there has been an error when loading data into the semantic model, there can be times when clicking on the View errors can either take a very long time to show those errors. Or in some cases it never shows you the error.

In this blog post I am going to show you an alternative way to quickly find the errors.

The column quality data preview option is absolutely worth keeping on at all times.

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