Book Image

Guide to NoSQL with Azure Cosmos DB

By : Gaston C. Hillar, Daron Yöndem
Book Image

Guide to NoSQL with Azure Cosmos DB

By: Gaston C. Hillar, Daron Yöndem

Overview of this book

Cosmos DB is a NoSQL database service included in Azure that is continuously adding new features and has quickly become one of the most innovative services found in Azure, targeting mission-critical applications at a global scale. This book starts off by showing you the main features of Cosmos DB, their supported NoSQL data models and the foundations of its scalable and distributed architecture. You will learn to work with the latest available tools that simplify your tasks with Cosmos DB and reduce development costs, such as the Data Explorer in the Azure portal, Microsoft Azure Storage Explorer, and the Cosmos DB Emulator. Next, move on to working with databases and document collections. We will use the tools to run schema agnostic queries against collections with the Cosmos DB SQL dialect and understand their results. Then, we will create a first version of an application that uses the latest .NET Core SDK to interact with Cosmos DB. Next, we will create a second version of the application that will take advantage of important features that the combination of C# and the .NET Core SDK provides, such as POCOs and LINQ queries. By the end of the book, you will be able to build an application that works with a Cosmos DB NoSQL document database with C#, the .NET Core SDK, LINQ, and JSON.
Table of Contents (13 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

Understanding rate limiting and throttling


If we hit the provisioned RU/s rate limit for any operation or query, the Cosmos DB service won't execute this operation and the API will throw a DocumentClientException exception with the HttpStatusCode property set to 429. This HTTP status code means that the request made to Azure Cosmos DB has exceeded the provisioned throughput and it couldn't be executed.

In some cases, the only way to execute the request would be to increase the provisioned throughput. For example, if we have a single operation that requires more than 1,000 RU/s but we have provisioned only 1,000 RU/s, there will be no way to execute the operation unless we increase the provisioned throughput. No matter the number of times we retry, the operation will always fail. Of course, we should avoid operations that require a huge amount of RU/s.

If we have two operations that require 501 RU/s each and we have provisioned only 1,000 RU/s, neither operation would be able to be executed...