Azure SQL Database Hyperscale: Powering a New Era of AI Apps

Hyperscale changed what Azure SQL Database can actually handle, and most teams haven't caught up to what that means yet. This session walks through what's new, not as a feature list but as a shift in how much headroom a database can realistically have without the usual scaling headaches.

Balmukund Lakhani, who's spent close to two decades inside Microsoft working directly with customers hitting these exact limits, covers the Hyperscale tier alongside where AI now sits inside Azure SQL Database itself. Copilot gets specific attention too, not as a novelty feature but as something that changes how people actually interact with their databases day to day.

Nineteen years inside Microsoft's support, field, and engineering functions means this isn't theoretical. It's built from what customers actually run into.

• What Hyperscale changes about scalability limits teams have learned to work around
• Where AI integration currently sits inside Azure SQL Database
• What Copilot actually does differently, beyond the demo version
• Resources and next steps for teams evaluating whether Hyperscale fits their workload

Most database scaling conversations still assume the old constraints. This session is about updating that assumption.

• What the Hyperscale tier changes about scalability and performance in Azure SQL Database
• How AI is being integrated directly into the Azure SQL Database platform
• What the Copilot feature enables for database management and querying
• Where to find resources for optimizing an existing Azure SQL Database setup

Azure SQL Database isn't scaling the way it used to. Hyperscale and the AI features built around it change what's realistic to expect from a database, and that's worth knowing before running into the old limits by accident.