I recently had the opportunity to talk a little PostgreSQL with the Salt Lake City PostgreSQL Meetup group (thank you for having me by the way). Great bunch of people who were really engaged and asked a lot of questions. On the way out of the event, I was chatting with one person (who had […]
A look at window functions in SQL and how they can be used to query data without the restrictions of a GROUP BY.
Older technology can introduce security issues, along with performance ones. Keeping your systems somewhat up to date is important for security.
This article dives into a fun (and interesting!) strategy for widening fixed-width columns in SQL Server, to reduce downtime, risk, and runtime at the time when a column’s data type needs to be changed.
Passwords are essential and also a problem in many organizations. Guidance has changed over the years and Steve has a few thoughts on what's recommended today.
Our major goal in terms of log maintenance for all databases under our care is to optimize for write performance, in order to support all activities that require SQL Server to write to the log, including data modifications, data loads, index rebuilds, and so on. However, it's also important to keep an eye on possible log fragmentation, which, as described previously, can affect the performance of processes that need to read the log, such as log backups and the crash recovery process.
I recently resolved an issue where a query pulling data from the last 30 days would time out due to the table’s size and the lack of a supporting index. Creating a supporting index is possible, but not ideal; it will be very large and may not be useful for most queries and use cases. I wonder how I could implement a filtered index that follows time and is always limited to the last n days.
Steve found someone using an interesting approach to get developers to address some technical debt.
This article looks at using the FP-Growth algorithm from Python to mine data in SQL Server.
Introduced in SQL Server 2025 CTP 1.3, the PRODUCT() function acts similarly to SUM(), but multiplies values rather than adds them. It is an aggregate function in SQL Server and therefore operates on a data set, rather than on scalar values.
By James Serra
Most enterprise questions do not live neatly in one place. The numbers may be...
Redshift keeps its SYS_* monitoring views for seven days in cluster, which is fine...
By Steve Jones
I was updating my session for the Data API Builder (DAB) recently, mostly to...
Comments posted to this topic are about the item Parameter Sensitive Plan Optimization vs....
Comments posted to this topic are about the item Hyperscale Replicas I
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What types of secondary replicas are available for the Azure SQL Database Hyperscale edition?
See possible answers