Despite being schema-agnostic, it’s worth thinking about modelling your Cosmos DB data to ensure high-performance and scalability.
Azure Cosmos DB is schema-agnostic by nature , which is great if we are working with unstructured or semi-structured data within our applications.
That being said, we need to give some consideration as to what type of data we will be storing in our Cosmos DB environments. In this video, I’ll be talking about:
- The limitations in approaching data modelling for Cosmos DB applications in the same way as we would when data modelling for applications that use relational databases.
- How we can use techniques like embedding or referencing our data in Azure Cosmos DB.
- How we can use a hybrid of both depending on the needs of our application.
- How we can even store different types of documents within the same container in Azure Cosmos DB.
If you have any questions, please feel to ask.
In my next video, I’ll be talking about Partitioning in Azure Cosmos DB, so if you want to learn how partitioning works in Azure Cosmos DB, make sure you subscribe!
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