It is very unlikely that your application does not store data in some form or shape. Whether it is a user profile, shopping cart, customer data or inventory details. Every application needs data. But every application requires something different. A social network needs to quickly identify similar interests and a financial application needs aggregated data and maybe trend analysis. And an online retailer is much more interested in targeting individual customers with recommendations.

For all these type of applications there is almost an unlimited number of options. Traditional relational databases like Oracle, SQL Server or Postgres build upon 50 year old principles. And no-sql options like Mongo looks much more developer friendly with schema on write principles. And today it looks like more purpose built database are finding their way to developers.

Yet, a disk is a disk and memory is memory. Storing data on disk is a trivial task for every database system. Understanding how this works and what you can control will help you better understand the performance of your application. Because, believe it or not, the performance of your application is based on how you model your data. Not which database system you use.

In this session I will show different applications with their own specific database requirements. I will show how to model this in a traditional relational database system. In my case, Microsoft SQL Server. But I believe the same principles apply to other traditional relational databases as well.

So if you want to learn how to model your data to maximize application performance, come to this session.