You have an OLTP database application which sustains a heavy mixed workload with lots of read and write transactions at the same time that it reports data to a client application.
Performance was fine for a long time, but it is not meeting your needs now that it must scale to much higher workloads. What should you do? In this real-world case study, you’ll learn about a series of technologies that provide unprecedented scalability, including data compression, In-
Memory OLTP, and clustered-partitioned columnstore indexes. We will walk you through a chronology of the application and database architecture, its changes over time, and the degree of performance improvement achieved with each new SQL Server feature applied. This session will teach you all about planning and implementing advanced SQL Server performance features and how each one impacts your system performance for applications with 100’s or 1000’s of concurrent users.
Here’s what you’ll learn in this session:
Goal 1: Learn how to plan, prepare for, and implement advanced features on SQL Servers, including data compression, In-Memory OLTP, and clustered-partitioned columnstore indexes.
Goal 2: See the performance impact of each of the major feature implementations as they relieve performance bottlenecks.
Goal 3: Learn about the trade-offs in applying major new features, tips and tricks, and other advice for achieving enterprise scale in your SQL Server applications.
Prerequisites: Intermediate experience with Microsoft SQL Server administration, application architecture, and SSMS.