Overview In this article, we will understand how we can connect to PostgreSQL using Node.js application. We will start with setting up PostgreSQL in our local system and perform basic CRUD operations to interact with the PostgreSQL database. Prerequisites To start with this, we need the following conditions to be met: Windows machine (or any […]
2025-07-24
1,209 reads
Taming Resource Hogs: Using SQL Server Resource Governor to Restrict User Group Consumption As a SQL Server professional, I've often encountered situations where a single, poorly written query or a resource-intensive application threatened to cripple the entire database server. Performance bottlenecks, unexpected slowdowns, and user complaints become the norm, making your life as a DBA […]
2025-07-24
717 reads
Fellow SQL Server professionals, I wanted to share some insights and start a discussion about the database design challenges we face when implementing Content Moderation Services in enterprise applications. As more organizations build user-generated content platforms, the backend data architecture becomes critical for efficient moderation workflows. Database Design Challenges for Content Moderation Services Performance at […]
2025-07-23
512 reads
This article describes the process to create a read-scale cross-platform SQL Server Availability Group where the primary is Linux and the secondary is Windows.
2025-07-23
361 reads
2025-07-23
2,942 reads
Introduction It was the week before Black Friday — the biggest online ad rush of the year. Our US-based ad-tech platform was gearing up for an insane traffic spike. Hundreds of real-time campaigns were about to go live across multiple brands, each with thousands of user sessions flowing through our system. Every incoming user impression […]
2025-07-22
2,324 reads
Take a basic look at database diagrams, what they are, and how to create one.
2025-07-21
579 reads
Unlocking Interoperability: A Guide to Foreign Data Wrappers in PostgreSQL and Aurora PostgreSQL AWS RDS As a database professional, I often encounter scenarios where data is fragmented across various systems. In today's distributed IT landscape, it's not uncommon for critical business information to reside in different databases, perhaps an on-premise PostgreSQL instance for legacy applications, […]
2025-07-21
63 reads
2025-07-18
5,742 reads
In this article, I wanted to test a common assumption we DBAs make – that adding INCLUDE columns to indexes is harmless. I created a FULL recovery test database with a realistic wide Orders table containing extra large VARCHAR columns to simulate an ERP workload. I ran updates and measured transaction log backup sizes before and after adding INCLUDE columns to a nonclustered index. The results shocked me. The update without INCLUDE columns generated a 10 MB log backup, while the same update with INCLUDE columns produced over 170 MB – a 17x increase in log volume. I explain why this happens: INCLUDE columns are physically stored in index leaf rows, so updates affecting them write bigger log records. I also clarify that updating key columns generates even more log than INCLUDE updates because it involves row movement (delete + insert), but INCLUDE updates still cost more log than if those columns weren’t indexed at all. The takeaway is clear – INCLUDE columns are powerful, but they silently increase transaction log generation, impacting backup sizes, replication lag, and DR readiness. Always measure their real cost before deploying to production.
2025-07-18
665 reads
In my previous post, I showed you how to build a snapshot backup catalog...
By Steve Jones
Train employees well enough that they could get another job but treat them well...
By Steve Jones
I needed to test a striped backup, so I decided to ask the AI’s...
Comments posted to this topic are about the item Create an HTML Report on...
Comments posted to this topic are about the item Why Data Modelling Still Matters...
Hi when i think of server hops , i think of how kerberos assists...
When I run this code, how many rows are returned?
DECLARE @meals NVARCHAR(1000) = N'夕食昼食朝食' DECLARE @s NVARCHAR(1) = N'食' SELECT value FROM STRING_SPLIT(@meals, @s) GOSee possible answers