Azure SQL Devs’ Corner
Voices from the Azure SQL PM Team, focusing on development and developers
Latest posts
Avoid T-SQL anti-patterns with the free T-SQL analysis tool
T-SQL Analyzer is a free, open-source, cross platform command line tool for identifying, and reporting the presence of anti-patterns and design issues in SQL Server T-SQL scripts. As a database developer, you can catch any potential bad practices and design problems very early in the project process - this ensures a frictionless path to deployment from development and test environments to production. The tool evaluates your scripts with more than 140 rules for design, naming and performance issues. The rules are created by Microsoft and the SQL Server community. If you already maintain your SQL scripts ...
Efficiently and Elegantly Modeling Embeddings in Azure SQL and SQL Server
Storing and querying text embeddings in a database it might seem challenging, but with the right schema design, it's not only possible, it's powerful. Whether you’re building AI-powered search, semantic filtering, or recommendation features, embeddings, and thus vectors, are now a first-class data type. So how do you model them well inside a database like SQL Server and Azure SQL? In this post, I’ll walk you through a practical, scalable strategy to store embeddings effectively—while keeping your schema clean, your queries readable, and your operations efficient. This blog post is part of a series of blogs ...
MSSQL Extension for VS Code: Introducing Schema Compare (Preview)
Overview We are excited to introduce Schema Compare in the MSSQL Extension for VS Code! It can be tedious to manually manage and synchronize different database versions. Enter Schema Compare, the powerful new feature for MSSQL in VS Code that transforms this tedious task into a seamless experience. With intuitive visualization that instantly highlights additions, removals, and modifications between schemas, you gain complete control over which changes to implement. Whether comparing live databases, dacpac files, or SQL projects, Schema Compare empowers you to synchronize database versions with precision and c...
Predictable LLM results with Structured Output and sp_invoke_external_rest_endpoint
OpenAI recently introduced a powerful new feature for developers: structured output using JSON Schema via the parameter. This makes it possible to request responses from a GPT-4o model that strictly match a given schema—no free-text, no guesswork. If you're working with Azure SQL, this is a game-changer. Combined with the stored procedure and SQL Server's built-in JSON functions, you can now: What Is Structured Output? By default, LLMs like GPT-4 return free-form text—which can be difficult to parse reliably. With structured output, you provide a JSON Schema along with your request, and the m...
Enhancing Search Capabilities in SQL Server and Azure SQL with Hybrid Search and RRF Re-Ranking
In today's data-driven world, delivering precise and contextually relevant search results is critical. SQL Server and Azure SQL Database now enable this through Hybrid Search—a technique that combines traditional full-text search with modern vector similarity search. This allows developers to build intelligent, AI-powered search experiences directly inside the database engine. Funny enough one of the key algorithms needed for implementing Hybrid Search, BM25, has been included in SQL Server is almost forever, without much fanfare: RAG pattern and similarity search is bringing it to the light. What Is Hybrid S...
SQL Conf() 2025 Highlights: So Much Developer Innovation!
For decades, SQL Server has been a cornerstone of data management, evolving to meet the needs of modern developers. What began as a traditional relational engine is now a cloud-enabled, AI-integrated platform designed for building real-world applications. SQL Server continues to meet developers where they are—offering tools, services, and capabilities that simplify complexity and support innovation across the stack. SQL Conf() 2025, held February 26, was a developer marathon built specifically for application developers. While DBAs and data engineers often lead the conversation, this event flipped the focu...
Secure APIs with Data API Builder, Keycloak, and SQL Server
In this article, we'll explore how to create a secure, on-premises API using Data API Builder (DAB), Keycloak, and SQL Server. You'll learn to set up JSON Web Token (JWT) authentication with Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC), and Row-Level Security (RLS), ideal for secure business scenarios. Want to replicate this setup?All the configuration files, SQL scripts, and Docker setup used in this article are available here: https://github.com/yougnoli/secure-onprem-api-dab-keycloak-sqlserver Technologies Overview What We'll Cover RBAC a...
Vector Search with Azure SQL, Semantic Kernel and Entity Framework Core
Vector databases like Qdrant and Milvus are specifically designed to efficiently store, manage, and retrieve embeddings. However, many applications already use relational databases like SQL Server or SQL Azure. In such cases, installing and managing another database can be challenging, especially since these vector databases may not offer all the features of a modern relational database like Azure SQL or SQL Server. This is where the new vector data type in SQL Azure becomes extremely useful. It allows you to create Retrieval-Augmented Generation (RAG) solutions by storing embeddings in the same place as y...
Build a Streamlit application with Fabric SQL Database
Building an application allows you to operationalize the data you have in Microsoft Fabric, such that it can be consumed by stakeholders in your organization to generate business insights. Streamlit is easy to use to build simple applications without needing to know front-end application frameworks like Flask, Django etc. It makes it easier to prototype and visualize your data in Microsoft Fabric with Streamlit framework. In this blog post we will show how to develop an app using Streamlit and Fabric SQL database. Consider a scenario that you are a data engineer in a retail company and want to keep track of y...