Customer-managed keys (CMK) in Fabric SQL Database (Generally Available)
Customer-managed keys (CMK) in Fabric SQL Database is a major step forward in empowering organizations to take control of their data security and compliance.
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Microsoft Fabric Updates Blog
SQL Server Management Studio (SSMS) 22.4.1 and GitHub Copilot in SSMS (Generally Available)
GitHub Copilot in SQL Server Management Studio (SSMS) now offers a few highly requested features and several bug fixes based on feedback items. Check out the full release notes to learn about the complete list of updates in the 22.4.1 release. We appreciate you taking time to file issues, share your requests, and upvote items; you’ll notice your feedback helped us shape this release, and will help us continue to evolve the GitHub Copilot in SSMS integration.
Batteries included: Database DevOps with SQL projects
Database changes shouldn’t be the last manual step in your release process. As teams adopt DevOps practices to ship application code faster and more reliably, the database has remained a sticking point—manual scripts, inconsistent deployments, and limited visibility into what changed and when. SQL projects change that by making database schema a first-class citizen in source control, CI/CD pipelines, and collaborative development workflows.
What’s new and improved for SQL database in Fabric (Generally Available)
Following the SQL database in Microsoft Fabric (Generally Available) at Microsoft Ignite in November 2025, customer adoption has accelerated. Organizations are modernizing SQL workloads, reducing operational overhead, and bringing operational data closer to analytics and AI. This next wave of capabilities builds on the preexisting pillars—Simplified, Autonomous & Secure, and Optimized for AI—driven directly by customer feedback.
Advancing Databases for the Next Generation of Applications
As organizations accelerate their AI adoption, the role of databases is fundamentally changing. It’s no longer enough to manage operational and analytical data separately. AI-driven applications demand a unified foundation where transactional and analytical data come together securely, in near real time, and at scale.
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