At Microsoft Build, SQL Server 2025 enters public preview with major enhancements in AI integration, performance, reliability and developer tools -- reaffirming Microsoft’s continued investment in its ...

Managing SQL Server across hybrid and multi-cloud environments has long posed a challenge for database administrators. With data sprawled across on-premises infrastructure, cloud platforms, and edge ...

From AI-driven attacks to cutting-edge vector search capabilities, 2026 is redefining how we secure, optimize, and manage SQL databases. New SQL Server features, evolving threat landscapes, and modern ...

Despite its steep licensing costs, SQL Server continues to prove its worth over open-source alternatives in some key areas. SQL Server is an expensive part of your IT stack -- SQL Server Enterprise ...

Microsoft unveiled .NET Aspire at the Build 2024 developer conference, describing it as an opinionated, cloud-ready stack for building observable, production ready, distributed, cloud-native ...

This voice experience is generated by AI. Learn more. This voice experience is generated by AI. Learn more. The Microsoft Security Response Center has confirmed that a SQL Server elevation of ...

Two zero-day flaws in the form of a denial of service (DoS) issue in .NET and an elevation of privilege (EoP) issue in SQL Server top the agenda for security teams in Microsoft’s latest monthly Patch ...

At Build 2025, SQL Server 2025 officially entered public preview. As one of the world’s most popular databases, this release continues a decades-long history of innovation with features made for ...

A step-by-step guide to deploying, configuring, and testing a multi-AZ, multi-region SQL Server FCI in the Azure cloud, complete with a PowerShell script that handles the networking configuration.

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.

Abstract: Labeling large datasets for constructing a text normalization system is cumbersome and time-consuming. Although some self-supervised learning models can reduce the amount of training data ...