Posts by this author

May 6, 2025
Post comments count1
Post likes count2

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 databa...

Azure SQLAIVectors
Apr 29, 2025
Post comments count0
Post likes count0

Private: Vector Support Public Preview now extended to Azure SQL MI

Announcing Vector Type and Functions in Azure SQL Managed Instance Public Preview We are thrilled to announce that Azure SQL Managed Instance now supports Vector type and functions in public preview.  Vector support and functions have been available in Azure SQL in public preview since December. Check out the detailed announcement Azure SQL Man...

Azure SQLAIVectors
Apr 21, 2025
Post comments count1
Post likes count1

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 SQ...

Azure SQLAI
Apr 7, 2025
Post comments count0
Post likes count2

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 directl...

AI
Mar 19, 2025
Post comments count1
Post likes count3

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 t...

Azure SQLAI.NET
Mar 14, 2025
Post comments count0
Post likes count3

Exploring SQL Server Integration with .NET Aspire: A Collection of Hands-On Samples

I'm happy to share a new GitHub repository with developers: azure-sql-db-aspire. This collection of eight hands-on examples demonstrates how to integrate SQL Server and Azure SQL with .NET Aspire, making it easier to build modern, cloud-native applications. Why .NET Aspire for SQL Server? .NET Aspire is a new opinionated, cloud-ready stack for .N...

Azure SQL.NETData API builder
Feb 18, 2025
Post comments count0
Post likes count1

Go passwordless when calling Azure OpenAI from Azure SQL using Managed Identities

Security is a significant topic today, and the ability to access a service requiring authentication without using an API key, password, or secret is a common request from those concerned about the security of a solution, which includes all of us. In today's digital landscape, cybersecurity threats are increasingly sophisticated and frequent, mak...

Azure SQLAISecurity
Feb 13, 2025
Post comments count0
Post likes count2

Database and AI: solutions for keeping embeddings updated

In the previous article of this series, it was discussed how embeddings can be quickly created from data already in Azure SQL. This is a useful starting point, but since data in a database changes frequently, a common question arises: “How can the vectors be kept updated whenever there is a change to the content from which they have been generated?...

Azure SQLAI
Feb 4, 2025
Post comments count7
Post likes count3

Storing, querying and keeping embeddings updated: options and best practices

Embeddings and vectors are becoming common terms not only for engineers involved in AI-related activities but also for those using databases. Some common points of discussion that frequently arise among users familiar with vectors and embeddings include: Let’s tackle each one of these questions one by one starting from the very...

AIVectors
Jan 23, 2025
Post comments count0
Post likes count1

Improve the “R” in RAG and embrace Agentic RAG in Azure SQL

The RAG (Retrieval Augmented Generation) pattern, which is commonly discussed today, is based on the foundational idea that the retrieval part is done using vector search. This ensures that all the most relevant information available to answer the given question is returned and then fed to an LLM to generate the final answer. While vector search...

Azure SQLAI