OUTER APPLY Fundamentals: Part 2
In Part 2 of this series we learn how OUTER APPLY can be used in your queries to return data, even when there are no matches between tables.
2026-08-12
2,980 reads
SQL Server
Stairway to Reliable Database Deployments Level 6 – Managing Changesets Over Time
As database changesets accumulate over time, they gradually become more than deployment artifacts. This level explores how a well-organized changeset library evolves into a replayable representation of the database’s structural history, supporting not only reliable deployments but also reconstruction, auditing, and long-term maintainability. Through practical examples and a real-world case study, it shows why maintaining coherent Create and Rollback scripts continues to provide value long after a successful production deployment.
2026-08-05
637 reads
CROSS APPLY Fundamentals: Part 1
Learn the basics of the CROSS APPLY operator with a few examples in this short piece.
2026-07-27
4,966 reads
TRY_PARSE vs TRY_CONVERT in SQL Server: From Basics to Practical Usage
This article shows how the TRY_PARSE() and TRY_CONVERT() functions can be used to handle data quality issues and ensure that your software continues to function without throwing errors.
2026-07-13
3,673 reads
SQL Server Enum Implementation: A Single-Row View Strategy for Avoiding Magic Values
Learn about an alternative strategy for avoiding hardcoded literal values in SQL Server queries by using single-row views designed to mimic enum behavior.
2026-06-26
3,197 reads
Concurrency and Baseline Control: Level 5 of the Stairway to Reliable Database Deployments
As database development scales across multiple contributors, concurrency becomes an inherent aspect of the process. Changes that are individually correct may still conflict when developed against a shifting baseline. This level introduces a disciplined approach to managing parallel changesets by controlling their scope, identifying overlap, and resolving conflicts through realignment. By ensuring that only one changeset retains its original baseline while others are adapted accordingly, deployments remain predictable and consistent. Once released, changesets are treated as immutable, and further evolution proceeds through new, forward-only changes.
2026-06-24
1,138 reads
Stairway to Reliable Database Deployments Level 4 – Preparing for Production Deployment
This level examines how a rehearsed changeset is transformed into production-ready deployment artifacts. By consolidating scripts into controlled execution units and validating the resulting artifacts, the approach ensures that production deployment remains predictable and aligned with what was proven during rehearsal.
2026-06-11 (first published: 2026-06-10)
1,108 reads
Understanding SQL Server PARTITION BY with Examples
Introduction When developers first learn SQL aggregation, they usually start with the GROUP BY clause. It works well for summary reports because it combines multiple rows into a single result for each group. For example, you can calculate total sales per region or average salary per department. The limitation of GROUP BY appears when you […]
2026-06-05
4,322 reads
How to Calculate Distance Between Coordinates in SQL Server
Learn a quick way to calculate distances without resorting to spatial calculations.
2026-05-08
2,392 reads
Stairway to Reliable Database Deployments Level 2 - Defining the Deployment Contract
Level 2 formalizes the behavioral guarantees that a changeset must provide in order to be safely deployed and rolled back. It introduces the deployment contract, checkpoint semantics, and the structural scope of Create and Rollback scripts. Data changes are addressed through a dedicated Update mechanism, with clear boundaries and limitations. By the end of this level, a changeset becomes a predictable and well-defined unit that can be reasoned about independently of execution context.
2026-06-11 (first published: 2026-05-06)
1,217 reads
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Hyperscale Replicas I
What types of secondary replicas are available for the Azure SQL Database Hyperscale edition?
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