{"id":2899,"date":"2024-02-14T09:08:11","date_gmt":"2024-02-14T17:08:11","guid":{"rendered":"https:\/\/devblogs.microsoft.com\/azure-sql\/?p=2899"},"modified":"2024-02-15T10:18:35","modified_gmt":"2024-02-15T18:18:35","slug":"build-highly-scalable-ai-ready-applications-on-azure-sql-database-hyperscale","status":"publish","type":"post","link":"https:\/\/devblogs.microsoft.com\/azure-sql\/build-highly-scalable-ai-ready-applications-on-azure-sql-database-hyperscale\/","title":{"rendered":"Build highly scalable, AI-ready applications on Azure SQL Database Hyperscale"},"content":{"rendered":"

Build highly scalable, AI-ready applications on Azure SQL Database Hyperscale<\/h2>\n

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<\/a> provides the performance, reliability and security you expect from Azure SQL \u2013 but at the same price as commercial open source<\/a> databases.<\/p>\n

SQL Database Hyperscale delivers consistently high performance at any scale, standing above the competition. Combined with a new lower price, choosing the right relational database for your next application just got easier in a market full of relational database management systems (RDBMSs).<\/p>\n

Faster is better<\/h2>\n

You can build your next app on many databases, including Amazon Aurora, but you\u2019ll want to take another look at Azure SQL Database Hyperscale. We partnered with Principled Technologies on a commissioned study<\/a> to compare Azure SQL Database Hyperscale performance with other cloud databases in the market. Principled Technologies\u2019 study clearly shows that Azure SQL Database Hyperscale scales to manage your most critical workloads, outpacing Amazon Aurora PostgreSQL by up to 68 percent in both performance and value<\/strong>.1<\/sup><\/p>\n

\"A<\/p>\n

Azure SQL Database Hyperscale outperforms Amazon Aurora in benchmark tests performed by Principled Technologies.<\/em><\/p>\n

The benchmark test used the HammerDB 4.8 open-source OLTP workload (TPROC-C), a widely recognized industry standard. Using the \u2018all warehouses\u2018 option, Principled Technologies performed three tests on IO intensive workloads with three different user counts of 64, 96, and 128 users, and a database size of 2.3TB. Azure SQL Database Hyperscale processed new orders much faster than Amazon Aurora for the same vCore configurations, even as transaction volume increased.<\/p>\n

Intelligent autoscaling for the coolest apps you can dream up<\/h2>\n

If you\u2019re a developer, you know the challenges of managing data growth, performance, and scalability for your applications. You need a database that can deliver fast query responses, scale up or down on demand and handle massive amounts of data \u2013 particularly when training AI models. But just how big of a database do you need? When starting out, you may not know.<\/p>\n

One may think that hyperscale<\/em> means hypersized<\/em>. It\u2019s better to think of SQL Database Hyperscale as the hyperflexible<\/em> solution designed for today\u2019s data-intensive innovations of any size, including the latest AI-ready SQL apps. With its flexible storage architecture, SQL Database Hyperscale grows as needed for your ever more intelligent apps. In fact, Hyperscale databases are not created with a defined max size, storage is allocated automatically\u2014and you are billed only for the storage capacity actually used. Regardless of the type of workload, you can take advantage of the high throughput, autoscaling storage, and fast backups, for improved processing times and price-performance efficiency. SQL Database Hyperscale is the solution that keeps up as your apps grow to serve millions of users.<\/p>\n

That\u2019s why performing rights nonprofit Broadcast Music, Inc.<\/a> (BMI) is using SQL Database Hyperscale to process ever-growing terabytes of data more efficiently and affordably.<\/p>\n

\u201cWe\u2019ve improved our processing times by a minimum of 20 percent and as much as several hundred percent in some system areas.\u201d\nGreg Walrath, BMI Executive Director of Enterprise Architecture<\/p>\n

Price-performance value is also why one of the world\u2019s largest logistics companies \u2013 DHL \u2013 use SQL Database Hyperscale to handle its projected growth. According to Jochen Fischer, Deutsche Post DHL Group Senior Software and Security Architect, \u201cThe primary motivation was the price tag for Azure. We found that it would save us a lot of money.\u201d<\/p>\n

Build AI-ready apps on Azure SQL Database<\/p>\n

Artificial intelligence (AI) is transforming the way businesses operate, innovate, and compete. Today, you can harness the power of AI through the close integration that Azure SQL Database has with the broader suite of AI-related services on Azure. Integration with Azure Open AI and Azure AI Search is powering new scenarios like vector search<\/a> and Retrieval Augmentation Generation (RAG) for working with large language models (LLMs). For example, you can create Azure OpenAI<\/a> service models for your applications and query your data more easily. You can also use SQL Database Hyperscale together with Azure AI Search<\/a> to train LLMs on your own data.<\/p>\n

Market Leading Database Capabilities<\/h2>\n

Azure SQL Database Hyperscale brings three decades of SQL innovation to developers, along with the cloud scale and the latest AI capabilities. Some salient features that differentiate SQL Hyperscale database layer from the competition include:<\/p>\n