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SQL Server 2025 with AI! Are You Ready? #SQLServer2025 #MicrosoftSQL #SQLAI #VectorSearch #SQLServerCopilot #MicrosoftFabric #DataEngineering #DatabaseUpdates #TechUpdates #decodeites #mssqlfun #mssqlserver #mssql #rohitgarg Explore the future of databases with SQL Server 2025 — now supercharged with AI, automation, and next-gen features that redefine data management and analytics. In this video, we break down the Top 10 Features of SQL Server 2025, including built-in AI capabilities, vector search, Copilot in SSMS, and seamless integration with Microsoft Fabric and Azure AI. Whether you're a data engineer, DBA, or tech enthusiast, this is your ultimate guide to what's new and what's next! 🔟 Top 10 Features in SQL Server 2025 🤖 Built-in AI Capabilities – Run AI models directly in SQL Server with Azure AI, OpenAI, LangChain & Semantic Kernel. 🧠 Vector Data Type & Search – Store embeddings, enable semantic search, and power RAG workflows. 💬 Copilot in SSMS – Use natural language to write and explain SQL queries. 🔄 Change Event Streaming – Real-time DML tracking to Azure Event Hubs in JSON/Avro. 🌐 Mirroring to Microsoft Fabric – Hybrid cloud analytics with real-time dashboards. ⚡ Optimized sp_executesql – Faster dynamic SQL with reduced compilation storms. 📦 External AI Model Management – Register and call AI models via REST using T-SQL. 🔍 Vector Indexing with DiskANN – High-speed nearest neighbor search for large vector sets. 📊 Improved Query Store & IQP – Smarter performance insights and plan stability. 🧩 Expanded Language & Platform Support – Better cross-platform compatibility (Linux, containers, Azure). Blog: https://mssqlfun.com/ Channel: https://m.youtube.com/decodeites Blog Post: https://mssqlfun.com/2025/06/02/sql-server-2025-is-here-ai-just-changed-everything/ Detailed Description: The Future of SQL Server: AI, Automation, and the Next Generation of Databases ### 🔟 **Top 10 Features in SQL Server 2025** 1. **Built-in AI Capabilities** - Run AI models directly in the SQL engine. - Integrates with Azure AI, OpenAI, LangChain, and Semantic Kernel. 2. **Vector Data Type & Vector Search** - Store and query vector embeddings. - Supports semantic search and RAG (Retrieval-Augmented Generation) patterns. 3. **Copilot in SQL Server Management Studio (SSMS)** - Natural language interface to generate and explain SQL queries. - Boosts productivity and learning. 4. **Change Event Streaming** - Real-time DML change tracking (insert, update, delete). - Streams changes to Azure Event Hubs in JSON or Avro format. 5. **Mirroring to Microsoft Fabric** - Seamless data replication from SQL Server to Microsoft Fabric. - Enables hybrid cloud analytics and real-time dashboards. 6. **Optimized `sp_executesql`** - Reduces compilation storms. - Improves performance for dynamic SQL execution. 7. **External AI Model Management** - Register and manage AI models using T-SQL. - Call models via REST endpoints for inference. 8. **Vector Indexing with DiskANN** - High-performance approximate nearest neighbor search. - Efficient for large-scale vector data. 9. **Improved Query Store & Intelligent Query Processing** - Enhanced query performance insights. - Better plan stability and regression detection. 10. **Expanded Language & Platform Support** - Broader support for development languages and platforms. - Improved cross-platform compatibility (Linux, containers, Azure). Ai for database,Ai for sql server,Ai ready,Ai sql server,SQL Server 2025,ai,ai database,ai database tools,ai sql,ai sql tools,data analysis,data analyst,data analyst roadmap,data tools,database ai,database management,database optimization,database tools,enterprise database,microsoft sql server,performance tuning,sql performance,sql server 2025,sql server ai,sql tutorial,structured query language,database with ai,how sql server 2025 using ai

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