Azure SQL Devs’ Corner
Voices from the Azure SQL PM Team, focusing on development and developers
Latest posts
Stored Procedure Caching in Data API builder Now Supported
Announcing Procedure Cache Data API builder (DAB) has long supported Level 1 cache for tables and views. Level 1 is an in-memory cache that automatically stores frequent queries or slow-changing data in the API layer, bypassing several database queries. Today, Data API builder (DAB) also supports Level 1 cache for stored procedures. This is important. Minimizing long-running procedure calls can dramatically increase the number of concurrent calls your Data API can support. How does it get configured? The Data API builder (DAB) settings file configures cache at both the global level (under the runtime ...
Hot Reload in Data API builder Now Available
Announcing Hot Reload In a recent release, Data API builder (DAB) announced support for Hot Reload. This allows developers to modify the configuration file, save it and see the impact of those changes without restarting the engine. This tightens the loop, allowing developers to tune their implementation without waiting for needless tear down/set up operations. How is this useful? Getting your REST API just right is tricky. As you manipulate REST paths and settings, hit refresh in Swagger to see your changes and keep testing. Hot reload makes REST configuration faster and easier. Getting your GraphQL s...
Introducing Change Event Streaming: Join the Azure SQL Database Private Preview for Change Data Streaming
In a world where digital transformation is accelerating, the ability to integrate and process real-time data from diverse sources is crucial for success. Organizations today depend on timely insights to enhance decision-making, improve operations, and foster innovation. To meet this need, we’re thrilled to announce the private preview of Change Event Streaming (CES), a new functionality that lets you stream data changes directly from your Azure SQL Database into Azure Event Hubs. Starting now, you can apply to join this preview program. Participants will have the chance to test CES on Azure SQL Database and Az...
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 is great for its specific use case - semantic search, which is approximate by nature - it fails when it comes to searching for precise questions, like "show me the latest 10 code samples" as that request can - and should - be answered precisely without the need for vec...
Extending Regular Expressions (Regex) Support on Azure SQL Managed Instance (MI)
We are happy to announce the Private Preview of Regular Expressions (Regex) support on Azure SQL Managed Instance (MI). This new feature brings powerful text processing capabilities to your SQL queries, enabling you to perform complex pattern matching and data manipulation with ease. Regex support in Azure SQL The Regex feature in Azure SQL follows the POSIX standard and is compatible with the standard regex syntax and supports a variety of regex functions, such as REGEXP_LIKE, REGEXP_COUNT, REGEXP_INSTR, REGEXP_REPLACE, and REGEXP_SUBSTR. The feature also supports case sensitivity, character classes, quantifi...
SQL Server Native Vector Search for .NET Developers
It seems that the majority of developers naturally believe this field of software development belongs to mathematics and Python developers, who originally started building the first solutions. However, .NET and C# provide a great foundation for building almost any kind of application on any platform in a highly professional way. In this post, we will show, step by step, how to build GenAI solutions in C#/.NET that leverage SQL Server's native vector search capabilities. Introduction In the space of Generative AI, large language models offer different types of functionalities, often categorized as Complet...
Building a RAG-Based Smart Memory Application with Azure SQL Database
Project Mission The way people work and manage information is changing rapidly in our digital age. More and more people are struggling to keep track of all the online resources they use daily. They need a better way to save, organize, and retrieve important information from websites, articles, and other online sources. This is especially true for knowledge workers, researchers, and students who often need to quickly access and synthesize information from many different places. Project Goal The primary goal of our project is to develop My Smart Memory, a full-stack web application that enables users to save U...
Embedding models and dimensions: optimizing the performance to resource-usage ratio
Since the release of vector preview, we've been working with many customers that are building AI solution on Azure SQL and SQL Server and one of the most common questions is how to support high-dimensional data, for example more than 2000 dimensions per vector. In fact, at the moment, the vector type supports "only" up to 1998 dimensions for an embedding. One of the impressions that such limitation may give, is that you cannot use the latest and greatest embedding model offered by OpenAI, and also available in Azure, which is the text-3-embedding-large model, as it returns 3072 dimensions. Well, that's not the...
Azure SQL ❤️ Python!
I recently presented at Python Day 2024 on Langchain integration. I created a slide deck that I believe can be useful beyond just the session, so I wanted to share it here for everyone's benefit. The deck covers the most common topics for a Python developer: The slide deck, which I created using the Sli.dev SDK, so that slide themselves are available online in a very easy to access format, is available here: The session covers a lot more than what is in the deck. It was recorded and is available for everyone to view: https://www.youtube.com/watch?v=_Tfej--_4-Q&a...