--- 格式版本: 2 标题: "AWS Transform for full-stack Windows modernization now supports offline schema transformation to Aurora PostgreSQL" 原文链接: "https://aws.amazon.com/about-aws/whats-new/2026/7/aws-transform-windows-sql-schema-aurora" 发布日期: "2026-08-03" 发布时间校准状态: "found" 发布时间需复核: "否" 发布时间来源: "llm:local:original_extracted_text" 发布时间证据: "第169行：Posted on: Aug 3, 2026" 发布时间校准原因: "正文中明确标注'Posted on: Aug 3, 2026'，符合文章发布时间定义，且无其他矛盾候选。" 发布时间校准置信度: "1" 发布时间候选数量: 2 发布时间严格候选数量: 0 发布时间原页读取状态: "source template page reused from URL open" 发布时间未找到原因: "" 发布时间校准时间: "2026-08-10T16:08:59+08:00" 发布时间仲裁状态: "confirmed" 发布时间仲裁尝试次数: 1 发布时间仲裁耗时毫秒: 5102 发现时间: "2026-08-10T15:59:04+08:00" 入库时间: "2026-08-10T08:09:05.026Z" 来源平台: "固定入口" 搜索渠道: "fixed_url" 搜索词: "https://aws.amazon.com/new" 匹配关键词: - "delivery" - "performance" 相关厂家: - "AWS" - "Microsoft" 相关专家: [] 内容类型: "网页" 抓取工具: "Jina Reader" 清洗工具: "Jina Reader Markdown + Defuddle/Readability 正文提取" 原始附件: [] AI优质: "否" AI打分: 5 AI分档: "非优质" AI质检状态: "不通过" AI打分理由: "资料完全无关超级节点/AI Rack等主题，仅涉及数据库迁移工具，不包含任何项目关注的技术或商业信号。" AI质检模型: "deepseek-v4-flash" AI质检时间: "2026-08-10T16:09:10+08:00" AI主题相关性: 0 AI来源权威性: 5 AI新颖性: 0 AI技术细节: 0 AI商业部署信号: 0 AI完整性: 0 采集批次: "2026年8月10日15点46分00秒" 采集批次ID: "20260810-154600-0560986a" 去重键: "https://aws.amazon.com/about-aws/whats-new/2026/7/aws-transform-windows-sql-schema-aurora" --- Title: AWS Transform for full-stack Windows modernization now supports offline schema transformation to Aurora PostgreSQL URL Source: https://aws.amazon.com/about-aws/whats-new/2026/7/aws-transform-windows-sql-schema-aurora Markdown Content: ## Select your cookie preferences We use essential cookies and similar tools that are necessary to provide our site and services. 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AWS Transform now converts SQL Server storage objects, powered by AWS DMS, and code objects (stored procedures) using an agentic, interactive experience. Enterprises modernizing legacy .NET applications and their dependent SQL Server databases can now start their modernization by directly uploading the Data Design Language (DDL) source files from their databases. With offline source transformation, customers upload SQL Server data design language (DDL) files, assess database and stored procedure complexity, and generate a customizable transformation plan. AWS Transform converts tables, schemas and converts code objects such as stored procedures and functions, validates functional equivalence, and deploys the converted schema to Aurora PostgreSQL. The same workflow transforms database dependent .NET applications to be PostgreSQL compatible .NET applications with updated connection strings, ADO.NET and Entity Framework data-access calls. To address remaining conversion issues, customers can iterate directly in the web console or hand off to their preferred IDE using the AWS Transform MCP server. A separate synthetic data workflow populates Aurora PostgreSQL with test data for end-to-end application validation. AWS Transform for full-stack Windows modernization and offline source transformation is available in US East (N. Virginia). To get started, you can go to [AWS Transform product page](https://aws.amazon.com/transform/windows/) or see [AWS Transform for full-stack Windows documentation](https://docs.aws.amazon.com/transform/latest/userguide/windows-full-stack.html). 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