Workflows of Highly Functional App & Data Engineering Teams

How does a highly functional development team manage enterprise data engineering? They focus on the core principles of Schema Management, Standards Enforcement, Database Testing, and Automated Incremental Deployment. Microsoft brings an agonizing menu of choices to architects and engineers; they can be a challenge to wade through. This session can help. Let’s review how some of the world’s largest and most critical app & data engineering teams handle change management, observability, and quality at enterprise scale.

Goals: • Understand how enterprise teams manage schema control, including versioning, migrations, and updates, to ensure data consistency across all environments. • Explore how enterprise teams ensure engineering quality through automated testing, code reviews, and standards enforcement. • Learn how enterprise teams automate reliable delivery through continuous integration and deployment, reducing errors and improving efficiency.

A Developer's Guide to Database Patterns

If you think of the database as a pain in the neck, you're not alone. But with some engineering rigor, you can level up your database game. This critical component of your architecture can benefit from the same practices as code — source control gates, unit testing, CI/CD automation, linting, quality measurements, and abstract repositories. In this session, learn the engineering best practices used by development teams whose databases aren't a pain in the neck. This session is a collection of patterns recently curated from many of Microsoft's largest and most demanding customers.

1. Learn how to apply software engineering practices to database development, including source control, gates, CI/CD automation, and repeatable deployments.
2. Understand how testing, linting, quality checks, and schema validation can reduce database risk before changes reach production.
3. Explore practical patterns for designing, organizing, and abstracting database access so teams can improve reliability, maintainability, performance, and cost.

Introducing the SQL MCP Server

Modern apps use language models, but how do those models safely interoperate with your company’s backend data without putting the business at risk? SQL MCP Server answers that question. It is Microsoft’s open source MCP server for secure access to SQL Server, Azure SQL, PostgreSQL, Cosmos DB, and MySQL, running in the cloud or on premises at enterprise scale. It provides a feature-rich database API designed to help models understand and work with your data while enforcing permissions, policies, and operational boundaries.

Built on the same high-scale engine that powers Microsoft Fabric’s own GraphQL API, SQL MCP Server is designed for both scale and developer productivity. With a rich inner loop and a cross-platform command line, it works just as well for enterprise workloads as it does for engineers innovating on the ground.

SQL ❤️ AI Agents

SQL is becoming a powerful foundation for agentic applications. In this session, we will look at how to prepare relational data for semantic search using external model embeddings, text chunking, and DiskANN through SQL Server’s vector index capabilities. Then we will show how SQL MCP Server gives agents, including agents built in Microsoft Foundry, governed access to that data through security boundaries, permissions, and practical guardrails.

You will leave with a practical understanding of how SQL Server can support modern AI application patterns while keeping enterprise data close, queryable, protected, and safe for agentic workloads.

1. Understand how to prepare relational data for semantic search using external model embeddings, text chunking, and SQL Server vector indexes.
2. Learn how SQL MCP Server enables agents, including agents in Microsoft Foundry, to access SQL data through governed and secure interfaces.
3. Explore practical guardrails for agentic workloads, including permissions, query boundaries, data protection, and database compute safety.

SQL ❤️ NoSQL Databases

SQL Server is no longer limited to rows and columns. In this session, we will explore how SQL can work naturally with NoSQL-style data using the binary JSON data type, JSON functions, JSON indexes, computed columns, triggers, and document-focused design patterns. We will look at techniques for querying and shaping JSON documents, handling large documents, responding to document changes, and combining relational structure with flexible document models.

We will also look beyond JSON to SQL Server’s broader semi-structured data support, including XML, Regular Expression support, Fuzzy Search, and other capabilities that help developers build flexible applications without abandoning the database engine they already trust.

1. Understand how SQL Server supports NoSQL-style document patterns using JSON, binary JSON, JSON methods, and JSON indexes.
2. Learn practical techniques for working with documents through computed columns, triggers, large document handling, and hybrid relational-document designs.
3. Explore broader semi-structured data support in SQL Server, including XML, Regular Expressions, Fuzzy Search, and related developer-focused capabilities.

SQL ❤️ Software Developers

SQL Server continues to invest in the application developer experience. In this session, we will look at enhancements across drivers, Entity Framework, modern SQL data types, Aspire integrations, Linux SQL containers, database projects, schema source control, CI/CD workflows, and Community Toolkit features for Data API builder. We will also explore how developers can access SQL securely through REST, GraphQL, and SQL MCP Server, while using the VS Code MSSQL extension to streamline the inner developer loop.

You will leave with a practical view of how SQL Server helps developers build modern applications faster, more securely, and with fewer gaps between local development, APIs, agents, schema changes, and production data.

1. Understand recent SQL Server developer investments across drivers, Entity Framework, modern data types, Aspire, and Linux containers.
2. Learn how database projects, schema source control, and CI/CD integrations help teams manage database changes with the same discipline as application code.
3. Explore how SQL MCP Server and the VS Code MSSQL extension improve agent access, local development, and the developer loop.

SQL ❤️ Multimodel Schemas

SQL Server continues to expand beyond a single way of modeling data. In this session, we will look at multimodel schema design across relational tables, documents, graph relationships, vectors, spatial data, and time-based data patterns. We will explore how these models can work together in one database, allowing developers to choose the right shape for each part of the application without splitting data across disconnected systems.

You will leave with a practical view of how SQL Server supports flexible schema design while preserving queryability, governance, indexing, security, and operational consistency.

1. Understand how SQL Server supports multimodel schemas across relational, document, graph, vector, spatial, and temporal patterns.
2. Learn when to use each model and how to combine them within a single application architecture.
3. Explore how indexing, query patterns, security, and governance apply across different data shapes in SQL Server.

What Every Developer Should Know About Relational Databases

Relational databases are the foundation of many of the applications developers build every day, but they are much more than tables and rows. In this session, we will introduce the core concepts behind relational database systems, including tables, columns, relationships, views, indexes, computed values, procedures, parameters, and functions. We will also look at more advanced capabilities such as materialized views, temporal tables, memory-optimized tables, performance tuning, scale, cost, and built-in database features that help applications grow.

You will leave with a practical understanding of what relational databases are, how they work, and why they remain one of the most important tools for building reliable, secure, and scalable applications.

1. Understand the core building blocks of relational databases, including tables, columns, relationships, views, indexes, procedures, and functions.
2. Learn how relational database features support performance, scale, security, cost control, and application reliability.
3. Explore modern database developer capabilities, including tools, drivers, libraries, endpoints, engines, and recent innovations that make relational databases easier to use in modern applications.