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SQLServerCentral Article

Database Architecture Considerations for Implementing Content Moderation Services

  • Article

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 […]

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2025-07-23

565 reads

SQLServerCentral Article

We Gave Memory-Optimized Tables a Hash Lookup — Then Tried Pattern Matching Instead

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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 […]

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2025-07-22

2,450 reads

SQLServerCentral Article

Unlocking Interoperability: A Guide to Foreign Data Wrappers in PostgreSQL and Aurora PostgreSQL AWS RDS

  • Article

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, […]

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2025-07-21

113 reads

SQLServerCentral Editorial

Life's Little Frustrations

  • Editorial

As with others, I've had to deal with death in the family recently. Some other family members are dealing with cancer (a few friends too). Happily none of us has recently been a disaster zone, but that's happened too. So yeah, big, nasty scary stuff happens in life. However, for most of us, most of […]

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2025-07-19

97 reads

SQLServerCentral Article

When INCLUDE Columns Quietly Inflate Your Transaction Logs

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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.

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2025-07-18

722 reads

SQLServerCentral Editorial

Databases and Disasters

  • Editorial

I was just reading about how the Philippines are working to update their databases in support of faster and better responses in the case of an emergency. While I do volunteer for some of the local emergency services, I'm right at the bottom of the heap as just a radio operator. I don't have any […]

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2025-07-18

118 reads

SQLServerCentral Editorial

Sometimes, Troubleshooting Is Hard

  • Editorial

I hop in the Jeep the other day and turn on my ham radio. Have I mentioned I'm a licensed amateur radio operator? Yeah, yeah, I know. I won't shut up about it. Ha! My call sign is KC1KCE. I haven't been on HF in a while, but I'm regularly on the air locally here […]

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2025-07-16

100 reads

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Question of the Day

The string_agg function

We create the following table and then insert some records in it:

create table t1 (
   id int primary key,
   category char(1) not null,
   product varchar(50)
);

insert into t1 values
(1, 'A', 'Product 1'),
(2, 'A', 'Product 2'),
(3, 'A', 'Product 3'),
(4, 'B', 'Product 4'),
(5, 'B', 'Product 5');
What happens if we execute the following query in both Sql Server and PostgreSQL?
select id, 
category, 
string_agg(product, ';')
                 over (partition by category order by id
                 rows between unbounded preceding and unbounded following) as stragg
from t1;

See possible answers