Using AI Features in Azure HorizonDB (In development - coming soon)
Store, retrieve, and integrate data for AI systems using Azure HorizonDB
Course Summary
Do you want to start working with AI-related features in Azure HorizonDB?
As these features are relatively new, the focus of this course is on design and architecture decisions that remain valid, even as individual features, syntax, and external AI services evolve. But we will show you how to achieve great outcomes right now. It does not aim to turn Azure HorizonDB into an AI platform, nor does it attempt to teach model training, data science, or vendor-specific AI tooling.
This course is about using Azure HorizonDB to store, retrieve, and integrate data for AI systems, in a way that is reliable, understandable, and operationally sound. We assume you already understand Azure HorizonDB fundamentals and are comfortable working with PostgreSQL and database design.
— Are you responsible for deciding where AI-related logic should live, and where it should not?
— Do you need to support vector search, retrieval, or AI integration without turning the database into an experimental system?
— Have you been asked whether Azure HorizonDB should be used for embeddings, RAG patterns, or AI orchestration, and wanted a clear answer that you can explain?
If that matches the kind of responsibility you have, you’re in the right place. You'll get clear explanations, hands-on exercises, and short quizzes to make sure you not only understand the concepts but can confidently apply them in real Azure HorizonDB environments. And while the practical exercises are optional, we strongly encourage completing them. They are designed to be straightforward and focused on realistic scenarios, rather than tooling complexity. Setup is easy. The main requirement is access to an Azure subscription where you can create an Azure HorizonDB resource.
