Azure SQL Devs’ Corner

Voices from the Azure SQL PM Team, focusing on development and developers

Model your Supply Chain in a Graph Database | Part 3

In Part 3 of our series, we delve into the rewards that graph databases bring to supply chain modeling. We explore the clarity achieved through the MATCH keyword, enabling precise communication between technical and business teams. Validation becomes seamless as stakeholders intuitively analyze the graph, uncovering missing relationships and enriching data.

Model your Supply Chain in a Graph Database | Part 4

In Part 4 of our series, we explore the power of graph visualization in understanding and analyzing supply chain data. Using tools like PowerBI and the force-directed graph visual, we transform our SQL Graph data into an interactive and shareable format. The visualization allows us to easily comprehend the relationships within the supply chain, make discoveries, and make informed decisions. With SQL Graph, we combine the familiarity of Azure SQL with the advantages of graph modeling, providing clarity and precision when communicating with stakeholders.

Change Tracking in Azure SQL Database

The Azure SQL Database has two main ways to track changes with data (rows/DML) as well as table changes. One of those methods is Change Tracking with the other being Change Data Capture. Today’s post will be going into depth on Change Tracking. Change Tracking and Change Data Capture So, what’s the difference between the two? Change Data...

CTEs, Views or Temp Tables?

I've just finished watching the video from the @GuyInACube about Common Table Expressions and I noticed that in several comments there was the request to explain what is the difference between Common Table Expressions, Views and Temp Tables. This is quite a common question, and it is time to give it a simple, concise, and clear answer...

Solving the River Crossing problem with SQL Graph

Graph theory and associated techniques are extremely powerful. Azure SQL allows native representation of graphs as node and edge tables, and provides breadth-first-search traversal for native path finding. This blog post demonstrates the ease of use, and great power of, these features by using them to solve the classic river crossing riddle!