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
1,263 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
874 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
539 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
368 reads
2025-07-23
3,876 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
2,369 reads
Take a basic look at database diagrams, what they are, and how to create one.
2025-07-21
816 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
77 reads
2025-07-18
5,868 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
680 reads
Data Céilí 2026 Call for Speakers is now live! Data Céilí (pronounced kay-lee), is...
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From T-SQL, without requiring an XEvent session, can I tell which deprecated features are being used on my instance?
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