Patterns & Practices for Scaling Windows Azure SQL Database
Cloud computing is distributed computing which requires thoughtful planning and delivery – regardless of the platform choice. Because of the inherent complexity of running services at scale, it is important to understand the behavior and performance of the cloud platform in which a database is hosted to match business performance and scale expectations and requirements. This session will look at different scenarios, patterns, and best practices for building scalable databases in Windows Azure SQL Database. We’ll also look at scale-up vs. scale-out models, horizontal partitioning, and some tips for dealing with some of the complexities of cloud database scalability including identity generation, working with relationships, and fan-out queries.
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Scott Klein is a Microsoft Data Platform Senior Technical Evangelist who leaves and breathes data. His passion for data technologies brought him to Microsoft in 2011 which has allowed him to travel all over the globe evangelizing SQL Server and Microsoft’s cloud data services. Prior to Microsoft Scott was one of the first 4 SQL Azure MVPs, and even though those don’t exist anymore, he still claims it. Scott has authored several books that talk about SQL Server and Windows Azure SQL Database and continues to look for ways to help developers and companies grok the benefits of cloud computing. He also thinks “grok” is an awesome word.
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