Azure SQL Hyperscale Unveiled
The Cloud SQL AI Database for Everyone
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Beschreibung
As organizations build increasingly data-driven and AI-powered applications, they need database platforms that can grow without sacrificing performance or resiliency. In this practical guide, Bob Ward, a Principal Architect on the Microsoft Azure Data team, takes readers inside Hyperscale's distributed architecture, showing how it uses the power of SQL Server to deliver the scale, performance, and resiliency required by modern cloud workloads.
You will learn how to deploy Hyperscale, build applications that use JSON, vectors, in-database RAG, AI agents, and GitHub Copilot, and leverage core capabilities such as serverless compute autoscaling, elastic pools, automatic storage growth, high availability and disaster recovery, named replicas, and zone redundancy. Practical design patterns demonstrate how teams can start small, scale as needed, and combine familiar SQL Server skills with new cloud-first, AI-ready techniques.
Whether you are modernizing existing applications or building new intelligent systems, this guide equips you to use Azure SQL Hyperscale as a flexible, reliable, AI-enabled cloud database platform for workloads at any scale.
What You Will Learn
- Deploy Azure SQL Hyperscale for workloads of any size
- Translate existing SQL Server skills to cloud-based development
- Understand the distributed architecture and internals of Hyperscale
- Build data-driven applications using JSON, vectors, RAG, and AI agents
- Develop Hyperscale solutions using GitHub Copilot and related tools
- Secure cloud data and implement high availability and disaster recovery strategies
- Optimize performance across Hyperscale workloads
- Apply practical design patterns for scalability, resiliency, and modernization
As organizations build increasingly data-driven and AI-powered applications, they need database platforms that can grow without sacrificing performance or resiliency. In this practical guide, Bob Ward, a Principal Architect on the Microsoft Azure Data team, takes readers inside Hyperscale's distributed architecture, showing how it uses the power of SQL Server to deliver the scale, performance, and resiliency required by modern cloud workloads.
You will learn how to deploy Hyperscale, build applications that use JSON, vectors, in-database RAG, AI agents, and GitHub Copilot, and leverage core capabilities such as serverless compute autoscaling, elastic pools, automatic storage growth, high availability and disaster recovery, named replicas, and zone redundancy. Practical design patterns demonstrate how teams can start small, scale as needed, and combine familiar SQL Server skills with new cloud-first, AI-ready techniques.
Whether you are modernizing existing applications or building new intelligent systems, this guide equips you to use Azure SQL Hyperscale as a flexible, reliable, AI-enabled cloud database platform for workloads at any scale.
What You Will Learn
- Deploy Azure SQL Hyperscale for workloads of any size
- Translate existing SQL Server skills to cloud-based development
- Understand the distributed architecture and internals of Hyperscale
- Build data-driven applications using JSON, vectors, RAG, and AI agents
- Develop Hyperscale solutions using GitHub Copilot and related tools
- Secure cloud data and implement high availability and disaster recovery strategies
- Optimize performance across Hyperscale workloads
- Apply practical design patterns for scalability, resiliency, and modernization
Who This Book Is For
Developers, IT professionals, and SQL Server practitioners who want to build data-driven, AI-powered applications using Azure SQL Hyperscale.
Guides SQL professionals into Azure SQL Hyperscale with clear skills translation for cloud workloads Reveals Hyperscale internals that power scale, performance, resiliency, and AI‑ready data workloads Delivers end‑to‑end patterns from deployment & AI development through security, resiliency, performance, & modernization
Autor*in
Bob Ward
Themen in »Azure SQL Hyperscale Unveiled«
vector search in cloud databases rag workflows for sql applications agentic rag patterns for developers ai agents for data driven apps autoscale cloud database operations cloud sql performance tuning cloud database high availability azure style database scaling patterns sql migration to cloud platforms secure cloud database configuration json data modeling in relational systems vector indexing and search patterns intelligent data application design relational database ai integration troubleshooting cloud sql workloads