Common use cases and scenarios for Azure Cosmos DBThis article provides an overview of several common use cases for Azure Cosmos DB. The recommendations in this article serve as a starting point as you develop your application with Cosmos DB. After reading this article, youll be able to answer the following questions What are the common use cases for Azure Cosmos DB What are the benefits of using Azure Cosmos DB for retail applications What are the benefits of using Azure Cosmos DB as a data store for Internet of Things Io. T systems What are the benefits of using Azure Cosmos DB for web and mobile applications Introduction. Azure Cosmos DB is Microsofts globally distributed database service. The service is designed to allow customers to elastically and independently scale throughput and storage across any number of geographical regions. Azure Cosmos DB is the first globally distributed database service in the market today to offer comprehensive service level agreements encompassing throughput, latency, availability, and consistency. The Azure Cosmos DB project started in 2. Project Florence to address developer pain points that are faced by large Internet scale applications inside Microsoft. Observing that these problems are not unique to Microsofts applications, we decided to make Azure Cosmos DB generally available to external developers in 2. Azure Document. DB. The service is used ubiquitously internally within Microsoft, and is one of the fastest growing services used by Azure developers externally. Get answers to frequently asked questions about Azure Cosmos DB, a globally distributed, multimodel database service. Learn about capacity, performance levels, and. Origin and OriginPro Introduction. 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Azure Cosmos DB is a global distributed, multi model database that is used in a wide range of applications and use cases. It is a good choice for any serverless application that needs low order of millisecond response times, and needs to scale rapidly and globally. It supports multiple data models key value, documents, graphs and columnar and many APIs for data access including Mongo. DB API, Document. DB API SQL, Graph API Gremlin, and Tables API natively, and in an extensible manner. The following are some attributes of Azure Cosmos DB that make it well suited for high performance applications with global ambition. Azure Cosmos DB natively partitions your data for high availability and scalability. Azure Cosmos DB offers 9. Azure Cosmos DB has SSD backed storage with low latency order of millisecond response times. Azure Cosmos DBs support for consistency levels like eventual, consistent prefix, session, and bounded staleness allows for full flexibility and low cost to performance ratio. No database service offers as much flexibility as Azure Cosmos DB in levels consistency. Azure Cosmos DB has a flexible data friendly pricing model that meters storage and throughput independently. Azure Cosmos DBs reserved throughput model allows you to think in terms of number of readswrites instead of CPUmemoryIOPs of the underlying hardware. Azure Cosmos DBs design lets you scale to massive request volumes in the order of trillions of requests per day. These attributes are beneficial in web, mobile, gaming, and Io. T applications that need low response times and need to handle massive amounts of reads and writes. Io. T and telematics. Io. T use cases commonly share some patterns in how they ingest, process, and store data. First, these systems need to ingest bursts of data from device sensors of various locales. Next, these systems process and analyze streaming data to derive real time insights. The data is then archived to cold storage for batch analytics. Microsoft Azure offers rich services that can be applied for Io. T use cases including Azure Cosmos DB, Azure Event Hubs, Azure Stream Analytics, Azure Notification Hub, Azure Machine Learning, Azure HDInsight, and Power. BI. Bursts of data can be ingested by Azure Event Hubs as it offers high throughput data ingestion with low latency. Data ingested that needs to be processed for real time insight can be funneled to Azure Stream Analytics for real time analytics. Data can be loaded into Azure Cosmos DB for adhoc querying. Once the data is loaded into Azure Cosmos DB, the data is ready to be queried. In addition, new data and changes to existing data can be read on change feed. Change feed is a persistent, append only log that stores changes to Cosmos DB collections in sequential order. The all data or just changes to data in Azure Cosmos DB can be used as reference data as part of real time analytics. In addition, data can further be refined and processed by connecting Azure Cosmos DB data to HDInsight for Pig, Hive, or MapReduce jobs. Refined data is then loaded back to Azure Cosmos DB for reporting. For a sample Io. T solution using Azure Cosmos DB, Event. Hubs and Storm, see the hdinsight storm examples repository on Git. Hub. For more information on Azure offerings for Io. T, see Create the Internet of Your Things. Retail and marketing. Azure Cosmos DB is used extensively in Microsofts own e commerce platforms, that run the Windows Store and XBox Live. It is also used in the retail industry for storing catalog data and for event sourcing in order processing pipelines. Catalog data usage scenarios involve storing and querying a set of attributes for entities such as people, places, and products. Some examples of catalog data are user accounts, product catalogs, Io. T device registries, and bill of materials systems. Attributes for this data may vary and can change over time to fit application requirements. Consider an example of a product catalog for an automotive parts supplier. Every part may have its own attributes in addition to the common attributes that all parts share. Furthermore, attributes for a specific part can change the following year when a new model is released. Azure Cosmos DB supports flexible schemas and hierarchical data, and thus it is well suited for storing product catalog data. Azure Cosmos DB is often used for event sourcing to power event driven architectures using its change feed functionality. The change feed provides downstream microservices the ability to reliably and incrementally read inserts and updates for example, order events made to an Azure Cosmos DB. This functionality can be leveraged to provide a persistent event store as a message broker for state changing events and drive order processing workflow between many microservices which can be implemented as serverless Azure Functions. In addition, data stored in Azure Cosmos DB can be integrated with HDInsight for big data analytics via Apache Spark jobs. For details on the Spark Connector for Azure Cosmos DB, see Run a Spark job with Cosmos DB and HDInsight. Gaming. The database tier is a crucial component of gaming applications. Modern games perform graphical processing on mobileconsole clients, but rely on the cloud to deliver customized and personalized content like in game stats, social media integration, and high score leaderboards. Games often require single millisecond latencies for reads and writes to provide an engaging in game experience. A game database needs to be fast and be able to handle massive spikes in request rates during new game launches and feature updates. Azure Cosmos DB is used by games like The Walking Dead No Mans Land by Next Games, and Halo 5 Guardians. Azure Cosmos DB provides the following benefits to game developers Azure Cosmos DB allows performance to be scaled up or down elastically.