Best practices for Azure Cosmos DB: Data modeling, Partitioning and RUs
For many newcomers to Azure Cosmos DB, the learning process starts with data modeling and partitioning. How should I structure my data? When should I co-locate data in a single container? Should I de-normalize or normalize properties? What’s the best partition key for my model? In this demo-filled session, we discuss the strategies and thought process one should adopt for modeling and partitioning data effectively in Azure Cosmos DB. Using a real-world example, we explore Cosmos DB key concepts – request units (RU), partitioning, and data modeling – and how their understanding guides the path to a data model that yields best performance and scalability.