Data Modeling and Partitioning in Azure Cosmos DB

For many newcomers to Azure Cosmos DB, the learning process starts with data modeling and partitioning. How should you structure your model? When should you combine multiple entity types in a single container? Should you de-normalize your entities? What's the best partition key for your data? In this session, we discuss the key strategies for modeling and partitioning data effectively in Azure Cosmos DB. Using a real-world NoSQL example based on the AdventureWorks relational database, we explore key Azure Cosmos DB concepts—request units (RUs), partitioning, and data modeling—and how their understanding guides the path to a data model that yields the best performance and scalability. Attend this session, and acquire the critical skills you'll need to design the optimal database for Azure Cosmos DB.

#CosmosDBConf #CosmosDB #NoSQL

[slavengaspar]

An excellent presentation, with an excellent style and measure. It is not too architecturally abstract, but it also does not delve deeply into the program code. Great choice of examples! It can serve as an excellent foundation or starting point for designing a large number of different applications.”

[mrjamiebowman]

his videos on Plural Sight are really good.

[hansrudolf]

Amazing presentation - a shame that this will probably get burried by some YouTube algorithm and never see the daylight ...

[chetan]

Thanks for this CosmosDb team and Lenni. The only thing that is missing is how to select the right API. Core vs MOngoDB?

another query for the sales orders could be : which products sell the best.

[anasw]

Each Micro service has its own database/container, I think the question is invalid from its concept to Microservice