SQL, MCP, JSON, and Vector Search Explained with Jerry Nixon | Adam Cogan | NDC Sydney 2026
Jul 10, 2026•Channel
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Published1 week ago
Duration21:18
Video IDio82qWhBm50
Languageen
CategoryScience & Technology
PrivacyPublic
Made for KidsNo
Video TypeRegular Video
Performance Metrics
Views37
Likes1
Comments0
Engagement Rate2.70%
Likes per 100 views2.70
Comments per 1K views0.00
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Description
📞 Contact us: https://bit.ly/4fAFrVx
In this interview from NDC, Adam Cogan sits down with Jerry Nixon to talk about the future of SQL Server and why it remains such a powerful platform for modern applications. Jerry explains how the SQL MCP Server helps AI agents securely connect to databases without developers needing to build and maintain custom APIs for every table and operation.
They also explore how SQL Server is evolving with smarter search capabilities, including fuzzy search, regex, full text, and semantic vector search. Jerry shares how developers can now store vectors directly in SQL, run similarity searches, and keep structured, document, and semantic data in one place instead of spreading it across multiple platforms.
The conversation also covers JSON vs XML, document database trade-offs, business logic in the database, and why SQL Server still competes strongly with Postgres. It’s a practical discussion for developers and architects who want to simplify their stack while taking advantage of modern AI and data features.
00:00 | Introduction
00:30 | Jerry Nixon on SQL and MCP Server
01:18 | Why MCP replaces custom database APIs
02:10 | One MCP for SQL, Postgres, Cosmos, and MySQL
02:35 | Token usage and why SQL MCP uses only seven tools
05:03 | Replacing CRUD code with Data API Builder
07:46 | Business logic in the database
09:24 | Fuzzy search, regex, full text, and semantic search
12:00 | Vector data type and semantic similarity in SQL
15:29 | JSON vs XML and SQL Server vs Postgres
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#SQLServer #JerryNixon #AdamCogan #MCP #AIAgents #VectorSearch #SemanticSearch #JSON #Postgres #SSWTV
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