SQL ConstantCare® Population Report: Fall 2025
In this quarter’s update of our SQL ConstantCare® population report, showing how quickly (or slowly) folks adopt new versions of SQL Server, the data is very similar to last quarter
2025-11-17
In this quarter’s update of our SQL ConstantCare® population report, showing how quickly (or slowly) folks adopt new versions of SQL Server, the data is very similar to last quarter
2025-11-17
Like many of you, I have often put strings together (concatenation) with a simple arithmetical operator: +. We have a few other ways to put strings together, but in SQL Server 2025, we have a new operator that allows us to put strings together. This is the double pipe (||) operator. This article looks at […]
2025-11-14
3,843 reads
This is the true story of a 64-core SQL Server brought down by poor assumptions about its data. A clustered index designed for neat, sequential IoT inserts was overwhelmed when the real readings arrived late, out of order, and in bulk. The same risk lurks in any high-write system with unpredictable insert patterns. This article shows what can go wrong and how to avoid it.
2025-11-14
Learn how you can create a logging module in Python that can be used to insert real-time records in a PostgreSQL database and display them on a dashboard.
2025-11-12
2,195 reads
I have data coming into my SQL Server database as JSON. Before I start parsing it which is quite intensive, I need to check if some values are present in the JSON. Is there a function I can use to do this? Let’s see what the new JSON_CONTAINS function in SQL Server 2025 can do.
2025-11-12
Learn about a MySQL feature that could be useful in some scenarios for SQL Server.
2025-11-10
4,418 reads
Discover how the FULL OUTER JOIN in SQL can simplify queries, improve performance, and solve real-world data problems
2025-11-10
This article takes a look at the changes in SQL Server 2025 to the SUBSTRING function.
2025-11-07
9,682 reads
Microsoft introduced the APPLY operator in SQL Server 2005. Similar to a JOIN, it allows correlation between two table expressions. The key difference between the JOIN and APPLY operators is when you have a table-valued expression on the right side and want to evaluate it for each row from the left table expression. Since they produce similar results, when do you choose an APPLY versus a JOIN?
2025-11-07
This article explains how to customize an extended events session in SQL Server Analysis Services for auditing and monitoring
2025-11-05
1,703 reads
When I put together the invitation for T-SQL Tuesday #202, I wasn't sure what...
By Steve Jones
My life has some crazy travel stretches for sure. Between speaking, office visits, customer...
In Part 1, we saw how ‘Vamana’ represents vectors as nodes, connects them with...
Comments posted to this topic are about the item Server-Level Table sizes
Comments posted to this topic are about the item Optional Parameter Plan Optimization in...
There is a table tmp_tab:
CREATE TABLE tmp_tab ( id int, val int );
INSERT INTO tmp_tab VALUES (1, 1), (2, NULL), (3, 3), (4, 4), (5, 5);You want to order the rows ids by the following expression:
ISNULL(val, id) + 1Which of the following queries produces the expected ordering and why? (Select all correct) See possible answers