Azure SQL Devs’ Corner
Voices from the Azure SQL PM Team, focusing on development and developers
Featured posts
Announcing LangChain integration for your SQL-based AI applications
In today's data-driven world, the ability to seamlessly integrate various technologies is crucial for efficient data management and analysis. We’re excited to a...
Latest posts
Introducing Regular Expression (Regex) Support in Azure SQL DB
We are pleased to announce the private preview of regular expressions (regex) support in Azure SQL Database. Regex is a powerful tool that allows you to search, manipulate, and validate text data in flexible ways. With regex support, you can enhance your SQL queries with pattern matching, extraction, replacement, and more. You can also combine them with other SQL functions and operators to create complex expressions and logic. This feature can help you to: The Regex feature in Azure SQL DB follows the POSIX standard and is compatible with the standard regex syntax and supports a variety of...
Empowering the SQLBits website with Azure SQL and Data API Builder
SQLBits is the biggest and most well-known data conference in UK and Europe. With several thousand people attending every year, and with more than 10 years of session recordings, it provides an amazing amount of knowledge to everyone who wants to learn anything around the Microsoft Data Platform. Be it on-premises, or on Azure, or the shiny new Fabric, SQLBits has something for you. In late 2023 the new SQLBits 2024 was unveiled, along with the updated website, during a very funny and engaging live event with the SQLBI folks. If you have missed the event, make sure to watch the recording here: Along with ...
Azure SQL Trigger Binding for Azure Functions goes GA
Azure SQL Database Engineering and Product Management would like to announce that Azure SQL Trigger Binding for Azure Functions is now generally available (GA). Catching Up As a quick refresher, the Azure SQL trigger uses SQL change tracking functionality to monitor a SQL table for changes and trigger a function when a row is created, updated, or deleted. It can be used in many scenarios such as change streaming from an Azure SQL database, participating in event-based architectures, as well as real time updating of web pages and applications. The GitHub samples repository is located here if you would like to tr...
NL2SQL with LangChain and Azure SQL Database
LangChain is an open-source framework for creating applications that use and are powered by language models (LLM/MLM/SML). In this post, basic LangChain components (toolkits, chains, agents) will be used to create a natural language to SQL prompt that will allow interactions with an Azure SQL Database; just ask the database what you want as if speaking to another person. Getting Started Looking at the python notebook used for this sample, you may notice in the repository there are 2. One is using OpenAI and the other is using Azure OpenAI. This post will be using the OpenAI notebook. The differences are...
Build highly scalable, AI-ready applications on Azure SQL Database Hyperscale
Build highly scalable, AI-ready applications on Azure SQL Database Hyperscale AI and cloud-native applications built for the future need a highly scalable, cloud native database with excellent price-performance. For applications operating on mission-critical relational data, Azure SQL Database Hyperscale provides the performance, reliability and security you expect from Azure SQL – but at the same price as commercial open source databases. SQL Database Hyperscale delivers consistently high performance at any scale, standing above the competition. Combined with a new lower price, choosing the right relational ...
Build your APIs with DAB using Containers – Part 2
Are you tired of spending countless hours building APIs from scratch? With Data API builder (DAB), you can create your API in just minutes! All you need to do is create a JSON configuration file to describe your database entities (tables, views, stored procedures, or collections) from your Azure SQL Database, SQL Server, Cosmos DB, PostgreSQL, or MySQL database. Using containers with DAB (Data API Builder for short) provides a consistent, isolated, portable, and lightweight local development experience that makes team collaboration easier. Once the local development is completed, one possible next step is t...
Using AI for Content Moderation with Azure SQL Database
In my previous posts, I have covered using Azure OpenAI services with Azure SQL Database via REST endpoints. This post with further explore that pathway by creating stored procedures you can use to encapsulate the REST calls and combine them with custom business logic for AI content moderation with Azure SQL Database. A Quick Introduction The services to being used in this post are the new Azure AI Content Safety service and the Azure AI Language service. Azure AI Content Safety is a solution designed to detect harmful user-generated and AI-generated content in applications and services. It can detect such cont...
Chat with your data in Azure SQL Database
Welcome to the exploration of how to chat with your data in Azure SQL Database. Being able to interact with your data more intuitively and conversationally can significantly enhance your data analysis and decision-making processes. This blog post will guide you through the process of setting up a chat interface for your Azure SQL Database, using an eCommerce database as an example. Whether you’re a data scientist, a developer, or just a curious learner, this guide will provide you with a new perspective on interacting with your data. Create Azure AI Search The first step is to create an Azure AI search resource...
Relationship Advice from Data API builder
Data API builder exposes REST endpoints for MySQL, PostgreSQL, Cosmos DB, SQL Server and Azure SQL. REST (Representational State Transfer) endpoints allow developers to easily query a single table, view or stored procedure. However, Data API builder also exposes GraphQL endpoints. Like REST, GraphQL returns data, but unlike REST, GraphQL can return data from multiple related tables in nested results. This includes one-to-many, many-to-many, and many-to-one relationships. This diagram illustrates a simple database that uses all three relationships. Data API builder supports each, but to do so it is required...