Azure SQL Dev Corner
Voices from the Azure SQL PM Team, focusing on development and developers
Latest posts
The Polyglot tax – Part 4
The Agent-Ready Database: Security, Backup, and MCP Part 4 of 4 – The Multi-Model Database Series This is the final post in a four-part series on multi-model databases in SQL Server 2025 and Azure SQL - exploring how the optimizer, storage engine, and security layer treat each data model as a first-class citizen under one roof. In Part 1: The Polyglot Tax, we described the trajectory: you spin up a database, point an agent at it, and start building fast. The complexity comes later - JSON, graph, vectors, analytics - and each new requirement tempts you to spin up another database. In Part 2: When JSON Met Gra...
Introducing SQL MCP Server
SQL MCP Server gives enterprises a secure, feature-rich way to enable agents to access data. This is accomplished without exposing the schema, risking consistency, or relying on fragile natural language parsing. SQL MCP Server is a feature of Data API builder, so deployments have a proven entity abstraction system, RBAC security at the API layer with Azure Key Vault integration, custom OAuth and Microsoft Entra support, first-level and second-level caching with integration with Redis and Azure Managed Redis, and complete instrumentation and telemetry with integration with Azure Log Analytics, Application Insights...
The Polyglot tax – Part 3
Vectors, Analytics, and the End of ETL Part 3 of 4 - The Multi-model Database Series In Part 1: The Polyglot Tax we laid out the fraud detection scenario: a transaction comes in, and before you approve or deny it you need five checks. Order history (relational). Device fingerprint (JSON). Connections to fraud rings (graph). Transactions that look like this one (vector similarity). Statistical baselines across millions of rows (analytics). Five data access patterns, five databases in the polyglot model, five sets of everything that can break. In Part 2: When JSON Met Graph we handled the first three. We store...
SQL code analysis in VS Code: Configure rules without editing your project file
SQL code analysis has been part of the SSDT workflow for a long time. Before deploying a schema change, you could run a set of static analysis rules against your project to catch potential issues, things like missing primary keys, deprecated syntax, or objects that could break under certain compatibility levels. It was one of those SSDT features that teams quietly relied on without thinking much about it. When developers started moving their SQL Database Projects workflow to VS Code, code analysis came with them. But configuring which rules to enable or disable required editing the .sqlproj file directly, not a ...
Manage SQL database schemas in VS Code: Publish dialog and item templates
Making schema changes often means jumping between tools. You write code in VS Code, then switch to a separate tool to deploy your changes : exporting a script, running it manually, or copy-pasting into a query editor. Either way, it pulls you out of your flow. With the latest updates to SQL Database Projects in VS Code, that context switching is no longer necessary. You can now manage and deploy schema changes to Azure SQL, SQL Server, or Fabric SQL databases without leaving your editor. What's new: Publish dialog and item templates We've added two features to the SQL Database Projects extension for VS Code th...
DiskANN Vector Index Improvements
Remember when we announced the Public Preview of DiskANN vector indexes back in November and mentioned that once you created the index, your table became read‑only? Yeah… about that... 😅 We shipped early because the demand for Vector search in SQL was overwhelming. We knew the constraints weren’t ideal, but we also knew the fastest way to get this into your hands was to iterate in public. You gave us feedback. Lots of it! And today, we’re excited to say: those major preview limitations are gone. We are happy to announce that the DiskANN Vector Index public preview just received a major upgrade, removing the in...
MSSQL Extension for VS Code: SQL Notebooks, AI-Powered Schema Design, Data API builder & More
The MSSQL extension for VS Code v1.41 continues to evolve, delivering features that make SQL development more integrated, more powerful, and more developer-friendly. In this release, we're introducing the Public Preview of Schema Designer with GitHub Copilot, Data API builder, and SQL Notebooks, along with the General Availability of Data-tier Application, Fabric integration, and SQL Database Projects static code analysis: seven capabilities that bring AI-powered schema design, instant API generation, interactive notebooks, and enterprise-grade tooling directly into your development workflow inside Visual Stu...
The Polyglot tax – Part 2
When JSON Met Graph Part 2 of 4 - The Multi-model Database Series A note on naming. Throughout this series, when we say "SQL Server 2025" we also mean Azure SQL. The multi-model capabilities we discuss - native JSON, graph, vector, and columnstore - are available across both the on-premises engine and the Azure SQL family. In Part 1 we described the moment every fast-moving project hits: the agent built your prototype in a morning, and now the product team wants features that do not fit neatly into relational tables. Device fingerprints arrive as nested JSON. The anti-fraud team needs to trace connection...
What questions will you ask your data agent?
Data API builder (DAB) 1.7+ delivers secure MCP-based CRUD access with deterministic, policy-enforced query generation and an upcoming aggregate tool that enables complex, production-safe analytical questions without exposing raw SQL to AI agents.
The Polyglot Tax
Part 1 of 4 - The Multi-model Database Series This is a four-part series about what happens when a single database engine handles relational, document, graph, vector, and analytical workloads natively - and what you stop paying for when it does. You spin up a database, point an agent at it, and start building. The first few tables go fast - users, orders, maybe a product catalog. The agent writes your CRUD, wires up the API, and you have a working prototype by lunch. Then the requirements come in. The product team wants semantic search. The fraud team needs to trace connections between accounts. Marketing wa...
MSSQL Extension for VS Code: Query Profiler, ADS Migration Toolkit & More
The MSSQL Extension for VS Code continues to evolve, delivering features that make SQL development more integrated, more powerful, and more developer-friendly. In version v1.40.0, we're introducing the ADS Migration Toolkit, Basic Database Management, Flat File Import, Database Backup & Restore, Database Object Search, and Query Profiler — six capabilities that bring seamless Azure Data Studio migration, essential database operations, and real-time performance monitoring directly into your development workflow inside Visual Studio Code. What’s new in MSSQL extension for VS Code v1.40 https://www.youtube.com...
Light up Multiple Databases with a Single API with Data API builder’s multi-source configuration
Data API builder (DAB) supports multi-source configurations Data API builder (DAB) connects to your database with a safe REST or GraphQL endpoint. But DAB is not limited to just one database. Using a multi-source configuration, you can connect to more than one database simultaneously. Learn more about Data API builder: https://aka.ms/dab/docs Multi-source configuration A multi-source configuration is one of DAB's most powerful features. There is no special requirement other than a valid connection string. This lets multiple databases take advantage of a single instance of DAB with REST and GraphQL, but al...
Federating Databases with Data API Builder Chaining
For decades, DBAs relied on linked servers to stitch data together. If you needed data from two places, you wired them up and moved on. It worked. It was straightforward. It felt native to SQL. But what if linked servers are not an option? What if policy blocks them? What if one of the systems is not SQL or lives in another cloud? How do you cross engines, environments, and ownership boundaries without turning your architecture into a science project? In most modern enterprises, the limitation is not SQL. It is usually more hidden things like governance, separation of duties, or risk management policy. Applicat...
Dear Copilot, can you help me with SQL?
Perhaps we missed it at first, but Copilot is more than comfortable with SQL. This goes beyond autocomplete. This is moving from nothing to a working database without leaving our tools. Have we really arrived? Yes, sort of. For database engineers and app engineers alike, we have crossed an important line. Making us more productive is easy for Copilot. Modern developers already lean on these models. Making Copilot productive is the real unlock. From schema design to publishing in Azure, the question is not whether Copilot can help, but how we 10x Copilot. Walking through a common workflow, this article makes few ...
Build Intelligent Apps with SQL: Join the SQL + AI Datathon
The SQL + AI Datathon is a hands‑on challenge designed to show how the foundations for building modern, intelligent applications with SQL. Over a set of guided missions and a focused open hack, you’ll learn how to combine SQL with embeddings, semantic search, and Retrieval Augmented Generation (RAG) to build real AI‑powered experiences. The SQL + AI Datathon puts SQL at the center of the architecture. You’ll learn how to: Who Should Participate? The SQL + AI Datathon is designed for: Learn Along the Way with the Reactor Series To help you succeed, the Datathon i...
Time Travel in Azure SQL with Temporal Tables
Applications often need to know what data looked like before. Who changed it, when it changed, and what the previous values were. Rebuilding that history in application code is tedious and error prone. This is especially valuable when exposing a database to an AI agent through MCP servers like SQL MCP Server, where information discovery matters. Learn more about SQL MCP Server at https://aka.ms/sql/mcp Azure SQL includes a built in feature that tracks row history automatically. Temporal tables let the database keep a full change history without triggers, audit tables, or custom logic. Working demo https...
Masking Sensitive Data in Azure SQL
Applications often need access to data without needing access to everything. Social Security numbers, email addresses, and phone numbers are common examples. Storing them is required. Exposing them broadly is not. This is especially valuable when exposing a database to an AI agent through MCP servers like SQL MCP Server, where safety and reversibility matter. Learn more about SQL MCP Server Azure SQL includes built-in features that let the database protect sensitive values automatically. The application does not decide what is visible. The database does. Working demo https://gist.github.com What We Ar...
Enable Soft Delete in Azure SQL
Sometimes applications need to remove data without actually losing it. Soft delete keeps rows in the database while making them invisible to normal application access. This is especially valuable when exposing a database to an AI agent through MCP servers like SQL MCP Server, where safety and reversibility matter. Learn more about SQL MCP Server Filtering on an column in every query is fragile. One missed filter exposes your data. Row Level Security enforces visibility rules inside the database so application code cannot bypass them. Working demo https://gist.github.com What We Are Building A table...