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Copilot.png","associationType":"TEASER","width":3152,"height":1764,"altText":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zOTkwMDY1LTUzMDE5NGlBNDY5NjJFRDA3Q0Q1ODE1?revision=5\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zOTkwMDY1LTUzMDE5NGlBNDY5NjJFRDA3Q0Q1ODE1?revision=5","title":"Try Copilot.png","associationType":"BODY","width":3152,"height":1764,"altText":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zOTkwMDY1LTUzMDE5Nmk3N0YyODc0ODBDOEI3QUZC?revision=5\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zOTkwMDY1LTUzMDE5Nmk3N0YyODc0ODBDOEI3QUZC?revision=5","title":"cosmoscopilot.png","associationType":"BODY","width":3145,"height":1721,"altText":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zOTkwMDY1LTUzMDE5OWlGODhDQjUzQkQ2M0RERUQz?revision=5\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zOTkwMDY1LTUzMDE5OWlGODhDQjUzQkQ2M0RERUQz?revision=5","title":"peripherals.png","associationType":"BODY","width":2567,"height":1413,"altText":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zOTkwMDY1LTUzMDIwM2k4QUM4Q0U0MTZCNjA3Mzky?revision=5\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zOTkwMDY1LTUzMDIwM2k4QUM4Q0U0MTZCNjA3Mzky?revision=5","title":"copilotpreview.png","associationType":"BODY","width":2463,"height":1579,"altText":null},"BlogTopicMessage:message:3990065":{"__typename":"BlogTopicMessage","subject":"How to Write NoSQL Queries with Copilot for Azure Cosmos DB","conversation":{"__ref":"Conversation:conversation:3990065"},"id":"message:3990065","revisionNum":5,"uid":3990065,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:210546"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" \n That’s why Microsoft has introduced Copilot for Azure Cosmos DB, an AI companion that simplifies how you work with Azure Cosmos DB. Copilot is an amazing AI-powered capability that can create Azure Cosmos DB NoSQL queries based on your natural language questions about your data. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":3617},"postTime":"2023-11-29T00:00:00.034-08:00","lastPublishTime":"2023-11-30T16:03:47.152-08:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" If you are a student or an entrepreneurial developer who wants to build modern data applications using Azure Cosmos DB, you might be wondering how to write NoSQL queries to access your data. NoSQL queries are different from SQL queries in that they use a document-based structure instead of a relational schema. This can make them more flexible and scalable, but also more challenging to learn and write. \n \n That’s why Microsoft has introduced Copilot for Azure Cosmos DB, an AI companion that simplifies how you work with Azure Cosmos DB. Copilot is an amazing AI-powered capability that can create Azure Cosmos DB NoSQL queries based on your natural language questions about your data. With Copilot, you don’t have to worry about the syntax or the structure of your NoSQL queries. Just type in your English-language question about your data and items in your Azure Cosmos DB collection, and Copilot will generate a query suggestion for you. Every generated query suggestion also contains a natural language explanation of the query, which can help you to understand and validate the query generated by Copilot. This empowers you to quickly and easily access your data stored in Azure Cosmos DB, and also learn how to write NoSQL queries better. \n Copilot is integrated with the Data Explorer’s query editor in the Azure portal. You can use it with any of your databases and collections that you have access to in Azure Cosmos DB, or you can use a sample database CopilotSampleDb from the SAMPLE DATA section to try it out. You can also provide feedback to the Copilot team by clicking on the thumbs up or thumbs down icons next to the suggestion. This will help inform the product team where the Copilot is performing well, and where there are opportunities for improvement. \n Copilot is currently in public preview, which means you need to enable it by your Azure subscription’s administrator in the Subscription’s preview features control. You can learn how to set up preview features in an Azure subscription here. Once you have enabled Copilot, you can follow these steps to use it: \n \n Open the Azure portal and navigate to your Azure Cosmos DB NoSQL resource. \n Navigate to the features blade under Settings and enable Copilot. \n Navigate to the Data Explorer query editor within the NoSQL API. \n Select the database and collection you’d like to query. \n Click on the Copilot icon and start asking questions about your data. Copilot will enter query suggestions into the query editor pane where you can also copy, edit, or execute them. \n \n That’s how you can use Copilot to query your data using natural language and learn how to write queries faster. Microsoft Copilot for Azure is an AI companion that unlocks the full power of Azure. We hope that Copilot will make your data querying experience more enjoyable and productive. \n Azure Cosmos DB is a fully managed and serverless distributed database for modern app development, with SLA-backed speed and availability, automatic and instant scalability, and support for open-source PostgreSQL, MongoDB, and Apache Cassandra. You can try Azure Cosmos DB for free here. \n Discover Microsoft Copilot for Azure, an AI companion that simplifies how you work with Azure Cosmos DB. Learn how to write NoSQL queries using natural language and get query suggestions with explanations. Try it now! \n The following table lists the limits for the Try Azure Cosmos DB for Free trial. Try Azure Cosmos DB free | Microsoft Learn \n \n \n \n \n Resource \n Limit \n \n \n \n \n Duration of the trial \n 30 days¹² \n \n \n Maximum containers per subscription \n 1 \n \n \n Maximum throughput per container \n 5,000 \n \n \n Maximum throughput per shared-throughput database \n 20,000 \n \n \n Maximum total storage per account \n 10 GB \n \n \n \n \n ¹ A new trial can be requested after expiration. ² After expiration, the information stored in your account is deleted. \n Learning Resources Get started with Azure Cosmos DB for NoSQL - Training | Microsoft Learn Execute queries in Azure Cosmos DB for NoSQL - Training | Microsoft Learn ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"4141","kudosSumWeight":2,"repliesCount":0,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDE","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zOTkwMDY1LTUzMDE5M2k4ODkwQzlENDZBODUyRUJF?revision=5\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDI","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zOTkwMDY1LTUzMDE5NGlBNDY5NjJFRDA3Q0Q1ODE1?revision=5\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDM","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zOTkwMDY1LTUzMDE5Nmk3N0YyODc0ODBDOEI3QUZC?revision=5\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDQ","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zOTkwMDY1LTUzMDE5OWlGODhDQjUzQkQ2M0RERUQz?revision=5\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDU","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zOTkwMDY1LTUzMDIwM2k4QUM4Q0U0MTZCNjA3Mzky?revision=5\"}"}}],"totalCount":5,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"coverImage":null,"coverImageProperties":{"__typename":"CoverImageProperties","style":"STANDARD","titlePosition":"BOTTOM","altText":""}},"Conversation:conversation:3783530":{"__typename":"Conversation","id":"conversation:3783530","topic":{"__typename":"BlogTopicMessage","uid":3783530},"lastPostingActivityTime":"2023-04-04T02:45:37.363-07:00","solved":false},"Category:category:AzureDatabases":{"__typename":"Category","id":"category:AzureDatabases","displayId":"AzureDatabases"},"Blog:board:AzureDataFactoryBlog":{"__typename":"Blog","id":"board:AzureDataFactoryBlog","displayId":"AzureDataFactoryBlog","nodeType":"board","conversationStyle":"BLOG","title":"Azure Data Factory Blog","shortTitle":"Azure Data Factory Blog","parent":{"__ref":"Category:category:AzureDatabases"}},"User:user:175989":{"__typename":"User","uid":175989,"login":"Mark Kromer","registrationData":{"__typename":"RegistrationData","status":null},"deleted":false,"avatar":{"__typename":"UserAvatar","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/dS0xNzU5ODktMTMzMjE4aUE2NEZBNEVBN0RFRjM2Q0Y"},"id":"user:175989"},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNzgzNTMwLTQ1NjAwMGk0MDM0OUU5QkFERjk5MjJB?revision=3\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNzgzNTMwLTQ1NjAwMGk0MDM0OUU5QkFERjk5MjJB?revision=3","title":"MarkKromer_0-1680190896536.png","associationType":"TEASER","width":1373,"height":650,"altText":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNzgzNTMwLTQ1NTk5OWlGMTMzRjY4NzUwMkQ3QkU2?revision=3\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNzgzNTMwLTQ1NTk5OWlGMTMzRjY4NzUwMkQ3QkU2?revision=3","title":"MarkKromer_1-1680190896541.png","associationType":"BODY","width":787,"height":789,"altText":null},"BlogTopicMessage:message:3783530":{"__typename":"BlogTopicMessage","subject":"Capture Changed Data From your Cosmos DB analytical store (Preview)","conversation":{"__ref":"Conversation:conversation:3783530"},"id":"message:3783530","revisionNum":3,"uid":3783530,"depth":0,"board":{"__ref":"Blog:board:AzureDataFactoryBlog"},"author":{"__ref":"User:user:175989"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" Making it super-easy to create efficient and fast ETL processing the cloud, Azure Data Factory has invested heavily in change data capture features. Today, we are super-excited to announce that Azure Cosmos DB analytics store now supports Change Data Capture (CDC), for Azure Cosmos DB API for NoSQL, and Azure Cosmos DB API for Mongo DB in public preview! \n \n ","introduction":"","metrics":{"__typename":"MessageMetrics","views":7980},"postTime":"2023-03-30T09:33:38.889-07:00","lastPublishTime":"2023-03-30T09:34:59.835-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" By Mark Kromer and revinchalil \n \n Making it super-easy to create efficient and fast ETL processing the cloud, Azure Data Factory has invested heavily in change data capture features. Today, we are super-excited to announce that Azure Cosmos DB analytics store now supports Change Data Capture (CDC), for Azure Cosmos DB API for NoSQL, and Azure Cosmos DB API for Mongo DB in public preview! \n \n This capability, available in public preview, allows you to efficiently consume a continuous and (inserted, updated, and deleted) data from the analytical store. CDC is seamlessly integrated with Azure Synapse Analytics and Azure Data Factory, a scalable no-code experience for high data volume. As CDC is based on the analytical store, it does not consume provisioned RUs, does not affect the performance of your transactional workloads, provides lower latency, and has lower TCO. \n \n \n \n Change Data Capture (CDC) with Analytical store. Click here for supported sink types on Mapping Data Flow. \n \n Consuming incremental data from Cosmos DB \n You can consider using analytical store CDC, if you are currently using or planning to use below: \n \n Incremental data capture using Azure Data Factory Data Flow or Copy activity \n One-time batch processing using Azure Data Factory \n Streaming Cosmos DB data \n Capturing deletes, intermediate changes, applying filters or projections or transformations on Cosmos DB Data \n \n Note that analytical store has up to 2 min latency to sync transactional store data \n Throughput isolation, lower latency and lower TCO \n Operations on Cosmos DB analytical store do not consume the provisioned RUs and so do not impact your transactional workloads. CDC with analytical store also has lower latency and lower TCO, compared to using ChangeFeed on transactional store. The lower latency is attributed to analytical store enabling better parallelism for data processing and reduces the overall TCO enabling you to drive cost efficiencies. \n \n No-code, low-touch, non-intrusive end-to-end integration \n The seamless and native integration of analytical store CDC with Azure Synapse and Azure Data Factory provides the no-code, low-touch experience. \n \n Incremental feed to the analytical platform of your choice \n Change data capture capability enables an end-to-end analytical story providing the flexibility to write Cosmos DB data to any of the supported sink types. It also enables you to bring Cosmos DB data into a centralized data lake where you can federate your data from diverse data sources. You can flatten the data, partition it, and apply more transformations either in Azure Synapse Analytics or Azure Data Factory. \n Setting up CDC in analytical store \n You can consume incremental analytical store data from a Cosmos DB container using either Azure Synapse Analytics or Azure Data Factory, once the Cosmos DB account has been enabled for Synapse Link and analytical store has been enabled on a new container or an existing container. \n \n On the Azure Synapse Data flow or on the Azure Data Factory Mapping Data flow, choose the Inline dataset type as “Azure Cosmos DB for NoSQL” and Store type as “Analytical”, as seen below. \n \n \n \n \n \n Capabilities \n In addition to providing incremental data feed from analytical store to diverse targets, CDC supports the following capabilities. \n \n Support for applying filters, projections, and transformations on the change feed via source query \n You can optionally use a source query to specify filter(s), projection(s), and transformation(s) which would all be pushed down to the analytical store. Below is a sample source-query that would only capture incremental records with Category = 'Urban', project only a subset of fields and apply a simple transformation. \n \n \n Select ProductId, Product, Segment, concat(Manufacturer, ‘-‘, Category) as ManufacturerCategory\n\nfrom c\n\nwhere Category = ‘Urban’\n\n \n \n \n Support for capturing deletes and intermediate updates \n Analytical store CDC captures deleted records and intermediate updates. The captured deletes and updates can be applied on sinks that support delete and update operations. The {_rid} value uniquely identifies the records and so by specifying {_rid} as key column on the sink side, the updates and deletes would be reflected on the sink. \n \n Filter change feed for a specific type of operation (Insert | Update | Delete | TTL) \n You can filter the CDC feed for a specific type of operation. For example, you have the option to selectively capture the Insert and update operations only, thereby ignoring the user-delete and TTL-delete operations. \n \n Support for schema alterations, flattening, row modifier transformations and partitioning \n In addition to specifying filters, projections, and transformations via source query, you can also perform advanced schema operations such as flattening, applying advanced row modifier operations and dynamically partitioning the data based on the given key. \n \n Efficient incremental data capture with internally managed checkpoints \n Each change in Cosmos DB container appears exactly once in the CDC feed, and the checkpoints are managed internally for you. This helps to address the below disadvantages of the common pattern of using custom checkpoints based on the “_ts” value: \n \n \n The “_ts” filter is applied against the data files which does not always guarantee minimal data scan. The internally managed GLSN based checkpoints in the new CDC capability ensure that the incremental data identification is done, just based on the metadata and so guarantees minimal data scanning in each stream. \n \n \n The analytical store sync process does not guarantee “_ts” based ordering which means that there could be cases where an incremental record’s “_ts” is lesser than the last checkpointed “_ts” and could be missed out in the incremental stream. The new CDC does not consider “_ts” to identify the incremental records and thus guarantees that none of the incremental records are missed. \n \n With CDC, there’s no limitation around the fixed data retention period for which changes are available. Multiple change feeds on the same container can be consumed simultaneously. Changes can be synchronized from “the Beginning” or “from a given timestamp” or “from now”. \n \n Please note that the linked service interface for Azure Cosmos DB for MongoDB API is not available on Dataflow yet. However, you would be able to use your account’s document endpoint with the “Azure Cosmos DB for NoSQL” linked service interface as a workaround until the Mongo linked service is supported. \n \n Eg: ON a NoSQL linked service, choose “Enter Manually” to provide the Cosmos DB account info and use the account’s document endpoint (eg: https://<accturi>.documents.azure.com:443/) instead of the Mongo endpoint (eg: mongodb://<accturi>.mongo.cosmos.azure.com:10255/) \n \n Next steps \n To learn more, please see our documentation on Change Data Capture in Azure Cosmos DB analytical store. \n ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"7244","kudosSumWeight":2,"repliesCount":1,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDE","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNzgzNTMwLTQ1NjAwMGk0MDM0OUU5QkFERjk5MjJB?revision=3\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDI","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNzgzNTMwLTQ1NjAwMGk0MDM0OUU5QkFERjk5MjJB?revision=3\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDM","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNzgzNTMwLTQ1NTk5OWlGMTMzRjY4NzUwMkQ3QkU2?revision=3\"}"}}],"totalCount":3,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"coverImage":null,"coverImageProperties":{"__typename":"CoverImageProperties","style":"STANDARD","titlePosition":"BOTTOM","altText":""}},"Conversation:conversation:1015605":{"__typename":"Conversation","id":"conversation:1015605","topic":{"__typename":"BlogTopicMessage","uid":1015605},"lastPostingActivityTime":"2019-11-26T23:28:34.113-08:00","solved":false},"Blog:board:IoTBlog":{"__typename":"Blog","id":"board:IoTBlog","displayId":"IoTBlog","nodeType":"board","conversationStyle":"BLOG","title":"Internet of Things Blog","shortTitle":"Internet of Things Blog","parent":{"__ref":"Category:category:IoT"}},"User:user:74424":{"__typename":"User","uid":74424,"login":"OlivierBloch","registrationData":{"__typename":"RegistrationData","status":null},"deleted":false,"avatar":{"__typename":"UserAvatar","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/dS03NDQyNC0yNDAxOTFpMDQ4QTI5RDA5QjlGNENDQQ"},"id":"user:74424"},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0xMDE1NjA1LTE1Nzc3NGk4ODc4N0ZCNzAzMUIwQjc0?revision=5\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0xMDE1NjA1LTE1Nzc3NGk4ODc4N0ZCNzAzMUIwQjc0?revision=5","title":"1097281592462201030_1097281592462201030.jpg","associationType":"TEASER","width":990,"height":536,"altText":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0xMDE1NjA1LTE1NzczMWk1RDA2NUU0NkM4NkJFRUYw?revision=5\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0xMDE1NjA1LTE1NzczMWk1RDA2NUU0NkM4NkJFRUYw?revision=5","title":"CosmosDB picture1.png","associationType":"BODY","width":1123,"height":684,"altText":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0xMDE1NjA1LTE1Nzc2M2lERTc2OTE5NjU3RkVGQkJE?revision=5\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0xMDE1NjA1LTE1Nzc2M2lERTc2OTE5NjU3RkVGQkJE?revision=5","title":"logical-partitions","associationType":"BODY","width":1206,"height":824,"altText":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0xMDE1NjA1LTE1Nzc2MmkwNDhCQkVGMEEwNjAzN0RE?revision=5\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0xMDE1NjA1LTE1Nzc2MmkwNDhCQkVGMEEwNjAzN0RE?revision=5","title":"request-units","associationType":"BODY","width":1000,"height":579,"altText":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0xMDE1NjA1LTE1Nzc2NGk4MUNDMjFCREQwOUNEQURE?revision=5\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0xMDE1NjA1LTE1Nzc2NGk4MUNDMjFCREQwOUNEQURE?revision=5","title":"changefeedoverview","associationType":"BODY","width":1201,"height":712,"altText":null},"BlogTopicMessage:message:1015605":{"__typename":"BlogTopicMessage","subject":"IoT Solutions and Azure Cosmos DB","conversation":{"__ref":"Conversation:conversation:1015605"},"id":"message:1015605","revisionNum":5,"uid":1015605,"depth":0,"board":{"__ref":"Blog:board:IoTBlog"},"author":{"__ref":"User:user:74424"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" \n Why should you care about Azure Cosmos DB when developing an IoT solution in Azure? Here is an attempt at explaining what Cosmos DB is great for in IoT apps. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":12147},"postTime":"2019-11-20T08:00:00.032-08:00","lastPublishTime":"2019-11-20T08:00:00.032-08:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Here are the 2 main reasons why Azure Cosmos DB is great for in IoT applications: \n \n Cosmos DB can ingest semi-structured data at extremely high rates. \n Cosmos DB can serve indexed queries back out with extremely low latency and high availability. \n \n For a fascinating history and in-depth technical outline of Cosmos DB, check out this blog by Dharma Shukla Founder of Azure Cosmos DB, Technical Fellow, Microsoft. \n The two primary IoT use cases for Cosmos DB are storing device telemetry and managing a device catalog. Read on to learn key details and catch this Channel 9 IoT Show episode with Andrew Liu, Program Manager, Cosmos DB team: \n \n \n \n Storing device telemetry \n The first IoT use case for Cosmos DB is storing telemetry data in a way that allows for rapid access to the data for visualization, post processing and analytics. \n XTO Energy, a subsidiary of ExxonMobil, uses Cosmos DB for this exact scenario. The company has 50,000 oil wells generating telemetry data like flow rate and temperature at a high throughput. With lots and lots of bytes/second coming in, XTO DB uses Cosmos DB because of its fast, indexed data store, partitioning, and automatic indexing. See the architecture diagram below showing how Cosmos DB fits in their IoT solution. Note that data comes into Azure IoT Hub. Typically, you would position a hot store (with fast, interactive queries) and cold store behind IoT Hub. In this case, Azure Cosmos DB is used for the hot store. Read more about XTO Energy use of Azure Cosmos DB and Azure IoT. \n \n \n \n Device catalog \n A second IoT scenario that benefits using Cosmos DB is managing a device catalog for critical processes. This is where the low latency and \"always on\" guarantees of Cosmos DB comes in. Less than 10-ms latencies for both, reads (indexed) and writes at the 99th percentile, all around the world and 99.999% availability for multi-region writes! \n Azure Cosmos DB transparently replicates your data across all the Azure regions associated with your Cosmos account. Cosmos DB employs multiple layers of redundancy for your data managing partitioning for you. Learn more about Cosmos DB high availability. \n A real-life scenario example is that of an automobile manufacturer running an assembly line with high availability requirements. The manufacturer drives commands to robots that manufacture the cars. In order to ensure that the assembly line never stops, the manufacturer uses Cosmos DB to ensure extremely high availability and low latency. \n \n Getting started with Cosmos DB for IoT \n There are four “must-know” aspects that IoT developers need to understand to work with Cosmos DB: \n \n Partitioning: The first topic an IoT developer needs to understand is partitioning. Partitioning is how you will optimize for performance. Cosmos DB does the heavy lifting for you taking care of partition management and routing in particular. What you will need to do is choose a partition key that makes sense during design. The Partition key is what will determine how data is routed in the various DB partitions by Cosmos DB and needs to make sense in the context of your specific scenario. The Device Id is generally the “natural” partition key for IoT applications. Learn more on partitioning. \n \n \n \n \n Request Units (RUs): The second topic an IoT developer needs to understand is Request Units. A Request Unit (RU) is the measure of throughput in Azure Cosmos DB. RUs are compute units for both performance and cost. With RUs, you can dynamically scale up and down while maintaining availability, optimizing for cost, performance and availability at the same time. RUs offer programmatic APIs for scenarios like batch jobs. Learn more about Request Units. \n \n \n \n \n Time to Live: The third topic IoT developers should understand is Time-to-Live or TTL. With TTL, Azure Cosmos DB provides the ability to delete items automatically from a container after a certain period of time. With the right understanding and use of TTL settings in Cosmos DB, and benefiting from the free deletes, you will save 50% compared to systems that charge IOPs for deletes. Learn more about Time to Live. \n \n \n \n Change Feed: The final “need to know” topic is change feed. A common design pattern in IoT is to use changes to the data to trigger additional actions. Change feed support in Azure Cosmos DB works by listening to an Azure Cosmos container for any changes. It then outputs the sorted list of documents that were changed in the order in which they were modified. The change feed is a single source of truth. You will avoid consistency issues across multiple systems when using it correctly. Learn more about change feed. \n \n \n \n Try a hands-on lab \n Not convinced yet? Try a hands-on lab. In the lab, you will use Azure Cosmos DB to ingest streaming vehicle telemetry data as the entry point to a near real-time analytics pipeline built on Cosmos DB, Azure Functions, Event Hubs, Azure Databricks, Azure Storage, Azure Stream Analytics, Power BI, Azure Web Apps, and Logic Apps. \n \n ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"5171","kudosSumWeight":1,"repliesCount":5,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDE","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0xMDE1NjA1LTE1Nzc3NGk4ODc4N0ZCNzAzMUIwQjc0?revision=5\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDI","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0xMDE1NjA1LTE1NzczMWk1RDA2NUU0NkM4NkJFRUYw?revision=5\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDM","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0xMDE1NjA1LTE1Nzc2M2lERTc2OTE5NjU3RkVGQkJE?revision=5\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDQ","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0xMDE1NjA1LTE1Nzc2MmkwNDhCQkVGMEEwNjAzN0RE?revision=5\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDU","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0xMDE1NjA1LTE1Nzc2NGk4MUNDMjFCREQwOUNEQURE?revision=5\"}"}}],"totalCount":5,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"coverImage":null,"coverImageProperties":{"__typename":"CoverImageProperties","style":"STANDARD","titlePosition":"BOTTOM","altText":""}},"Conversation:conversation:895730":{"__typename":"Conversation","id":"conversation:895730","topic":{"__typename":"ForumTopicMessage","uid":895730},"lastPostingActivityTime":"2019-10-06T09:17:10.945-07:00","solved":false},"Forum:board:Azure":{"__typename":"Forum","id":"board:Azure","displayId":"Azure","nodeType":"board","conversationStyle":"FORUM","title":"Azure","shortTitle":"Azure","parent":{"__ref":"Category:category:Azure"}},"User:user:398136":{"__typename":"User","uid":398136,"login":"narenan","registrationData":{"__typename":"RegistrationData","status":null},"deleted":false,"avatar":{"__typename":"UserAvatar","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/dS0zOTgxMzYtMTY4MzQ4aUU0OTEwQURDQ0U1Nzc2ODE"},"id":"user:398136"},"ForumTopicMessage:message:895730":{"__typename":"ForumTopicMessage","subject":"Tweet Sentiment Analytics made easy by Azure Services","conversation":{"__ref":"Conversation:conversation:895730"},"id":"message:895730","revisionNum":1,"uid":895730,"depth":0,"board":{"__ref":"Forum:board:Azure"},"author":{"__ref":"User:user:398136"},"metrics":{"__typename":"MessageMetrics","views":663},"postTime":"2019-10-06T09:17:10.945-07:00","lastPublishTime":"2019-10-06T09:17:10.945-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" I have written an article that explains how you can perform Tweet Sentiment Analytics using services from the Azure cloud. You can find the article on https://www.linkedin.com/pulse/tweet-sentiment-analytics-made-easy-azure-services-narendra-angane \n 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That Time – Get Set For Your Friday Five","conversation":{"__ref":"Conversation:conversation:428579"},"id":"message:428579","revisionNum":3,"uid":428579,"depth":0,"board":{"__ref":"Blog:board:mvp-blog"},"author":{"__ref":"User:user:300426"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" First published on MSDN on Feb 02, 2018 Persistent Storage And Volumes Using Kubernetes On Azure With AKS Or Azure Container Service Pascal Naber helps companies embrace Microsoft Azure and build large scale distributed systems with modern architectures based on microservices ","introduction":"","metrics":{"__typename":"MessageMetrics","views":434},"postTime":"2019-04-10T08:16:39.544-07:00","lastPublishTime":"2019-05-03T16:36:08.763-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" First published on MSDN on Feb 02, 2018 \n \n \n \n \n Persistent Storage And Volumes Using Kubernetes On Azure With AKS Or Azure Container Service Pascal Naber helps companies embrace Microsoft Azure and build large scale distributed systems with modern architectures based on microservices. Pascal works as an Azure Cloud Consultant at Xpirit. He is the co-founder of the Dutch Azure Meetup and is awarded by Microsoft with the MVP award for Microsoft Azure. In his spare time he enjoys killing monoliths, just for fun. Follow him on Twitter @pascalnaber. \n \n \n \n Storing Event Grid Messages In Cosmos DB \n Howard S. Edidin has over twenty-five years of experience in delivering Enterprise Integration Solutions. Howard is a Microsoft Most Valuable Professional (MVP), and Microsoft Partner Technology Solutions Professional (P-TSP) for Comsos DB and IoT He is a member of these elite communities chosen to augment Microsoft's internal Technology Specialists team, and provide enterprise architectural guidance to Microsoft customers and community. Howard has authored several books; \"HL7 for BizTalk\" and an eBook for Microsoft \"HL7 FHIR on Azure.\" Follow him on Twitter @hsedidin . \n \n \n \n \n Sharepoint Migration Tool From Microsoft John Naguib is an Office Servers and Services MVP. He's also a Solution Architect and Senior Consultant, with a deep knowledge of SharePoint. In addition, he has a strong .net application development background and is knowledgable in Office 365, Azure and several Microsoft products. John is a recognized expert within the IT industry, as he's published several gold award articles on Microsoft TechNet blogs and spoken at several events. He is based in Egypt. Follow him on Twitter @johnnaguib . \n \n \n \n \n What I Learned About Microsoft Doing DevOps: Part 1 – Moving To Agile And The Cloud \n Wouter de Kort works as an architect and consultant and lives in the Netherlands. He helps organizations stay on the cutting edge of software development. Wouter focuses on DevOps, Agile and Application Lifecycle Management. He authored the book DevOps on the Microsoft stack and some other books.Wouter is a Microsoft MVP and ALM Ranger. You can find him on on his blog at wouter de kort .com and at the various conferences where Wouter speaks. Follow him on Twitter @wouterdekort . \n \n \n \n \n \n Confronting Your Entity Framework Performance Fears \n Mitchel Sellers , based in Des Moines Iowa, enjoys spending time sharing his technology experience with others at events across the world. When not working with technology you will find him spending time with his family, traveling, or flying the skies above. Follow him on Twitter @mitchelsellers . \n \n \n \n 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Your First Planet-Scale App With Azure Cosmos DB","conversation":{"__ref":"Conversation:conversation:428809"},"id":"message:428809","revisionNum":3,"uid":428809,"depth":0,"board":{"__ref":"Blog:board:mvp-blog"},"author":{"__ref":"User:user:300426"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" First published on MSDN on Mar 13, 2018 Editor's note: The following post was written by Data Platform MVP Johan Åhlén as part of our Technical Tuesday series ","introduction":"","metrics":{"__typename":"MessageMetrics","views":715},"postTime":"2019-04-10T08:26:18.230-07:00","lastPublishTime":"2019-05-03T16:25:37.933-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" First published on MSDN on Mar 13, 2018 Editor's note: The following post was written by Data Platform MVP Johan Åhlén as part of our Technical Tuesday series. Daron Yondem of the Technical Committee served as the Technical Reviewer of this piece. Azure Cosmos DB is Microsoft’s distributed, multi-model cloud database service for managing data at planet-scale. It started in 2010 as “Project Florence,” to address developer pain-points that were faced by large Internet-scale applications inside Microsoft. In 2015, the first API was made available externally in the form of Azure DocumentDB. Finally, Azure Cosmos DB was launched in May 2017 and was recently honored in InfoWorld’s 2018 Technology of the Year Awards . This article will give you an introduction to Azure Cosmos DB and then take you through a sample scenario of building a globally scalable web application using Azure Cosmos DB and Azure Traffic Manager - called project Planetzine. But first, let’s delve into Azure Cosmos DB features and pricing Azure Cosmos DB comes with multiple APIs: \n \n \n SQL API , a JSON document database service that supports SQL queries. This is compatible with the former Azure DocumentDB. \n \n \n \n \n \n MongoDB API , compatible with existing Mongo DB libraries, drivers, tools and applications. \n \n \n \n \n \n Cassandra API , compatible with existing Apache Cassandra libraries, drivers, tools, and applications. \n \n \n \n \n \n Azure Table API , a key-value database service compatible with existing Azure Table Storage. \n \n \n \n \n \n Gremlin (graph) API , a graph database service supporting Apache Tinkerpop’s graph traversal language, Gremlin. \n \n \n This means that if you have an existing app that stores data in, for example, Gremlin, you can just point the app to your Azure Cosmos DB. What also makes Azure Cosmos DB stand out from other distributed database services is that it offers five different consistency models: The most popular one, the Session consistency model , comes with a read-your-own-writes guarantee, which means that a client will never get anything older than the last version of information that the client wrote. Some other great features of Azure Cosmos DB are: \n \n \n Stored Procedures \n \n \n \n \n \n User Defined Functions \n \n \n \n \n \n Triggers \n \n \n \n \n \n ACID support (within a single stored procedure or trigger) \n \n \n \n \n \n Designed for very high performance and scalability. \n \n \n \n \n \n Service Level Agreement that guarantees high availability and low latency. \n \n \n \n \n \n Automatic maintenance. Will handle growth or expansion to new geographic regions seamlessly in the background. \n \n \n \n \n \n Fully elastic. Scale up or down at any time. \n \n \n Azure Cosmos DB Architecture To start using Azure Cosmos DB, you need at least one account. Each account can have multiple databases (and each database can be of any model). Depending on the database model, the objects stored in the database are projected into containers/partitions/items. For instance, in the SQL API, the containers are called “Collections,” and the items are called “Documents.” Partitioning is optional, but without a partition key, there is a 10 GB limit to the database size and throughput is capped. I strongly recommend that you always use partitioning. Pricing The pricing has two components: \n \n \n Storage (per GB per month) \n \n \n \n \n \n Reserved RUs per second \n \n \n Performance (or “throughput”) is measured in RUs (“Request Units”). Each operation has an RU cost. Reading a 1KB item costs about 1 RU while writing and changing data costs more. The RUs represent a weighted measure of CPU, disk and network cost of your operations. If your requests demand higher RUs per second than you have reserved, they will be rate-limited (throttled). Note that, currently, the minimum billing is 400 RUs per second per container (or minimum 1000 RUs per second if you want to enable unlimited growth). Since the price is per container, you could keep costs down by letting multiple datatypes share the same container. If you distribute your data geographically, you will have to pay storage costs and reserved RUs for all the regions, so the total cost becomes approximately proportional to the number of regions where your data is distributed. The exact price details for your selected regions are available on the Azure pricing page . For development purposes, there are free options , but they, of course, have limitations. You can also download the Azure Cosmos DB Emulator and test your application locally. Now let’s get to work with ‘Project Planetzine’ Azure Cosmos DB is useful for a wide range of applications, but in some cases, Azure Cosmos DB is extra beneficial: \n \n \n Mobile applications, web applications or client applications that run globally \n \n \n \n \n \n Internet of Things \n \n \n \n \n \n Applications that contain existing code, which already uses any of the supported APIs (Mongo DB, Cassandra or Gremlin) \n \n \n \n \n \n When the application or service has to be globally scalable \n \n \n \n \n \n When there is a need for elasticity (to handle quick growth or bursts) \n \n \n \n \n \n When low latency, high availability, and high throughput is required (and has to be guaranteed by an SLA) \n \n \n \n \n \n When data consistency has to be clearly defined and guaranteed by an SLA \n \n \n Now, imagine that we are starting a global magazine, “Planetzine.” This global magazine has to be scalable, elastic - and data consistency is important. Also, we need to make sure the website of this global magazine is very fast for visitors worldwide, so we need the content to be replicated globally. Planetzine Architecture To serve website visitors from the nearest region, “Planetzine” uses: \n \n \n Azure Traffic Manager to route the visitors to the nearest regional website \n \n \n \n \n \n Regional websites (in any number of regions) \n \n \n \n \n \n Azure Cosmos DB database, which is replicated to multiple regions \n \n \n You can run this sample scenario with any number of regional websites. For best performance, and to have read operations stay within the visitors region, you should replicate your Azure Cosmos DB database to the same regions as the websites. Creating the Azure Services Let’s select the SQL API . Any API could be used, but my code is written for the SQL API. Note: All the APIs are native to Cosmos DB and equally supported by Microsoft. For your own applications, you should select the API that works best for you. Azure Cosmos DB In the Azure Portal, click “New” and chose Cosmos DB : \n \n \n Chose the SQL API. \n \n \n \n \n \n Leave “Enable geo-redundancy” unchecked, but after creation, click “Replicate data globally” to set up the data replication to the other regions of your choice. \n \n \n Consistency will by default be set to “Session”, which is fine. There will be no costs for your Azure Cosmos DB until you create a collection, and you don’t need to create any collection manually. Note that you will later need your URI, and PRIMARY KEY (or SECONDARY KEY), that can be found by clicking “Keys”: Azure Web Apps In the Azure Portal, click “New” and choose Web App: \n \n \n Chose Windows as OS. \n \n \n \n \n \n Create (or reuse) app service plans that are located in your desired regions. \n \n \n \n \n \n Note that setting a custom domain name on a web app that is integrated with Traffic Manager is only available for the Standard pricing tier (or higher). If you go to a lower tier, you will have to skip the Azure Traffic Manager. \n \n \n \n \n \n You should create web apps in the same regions that you are replicating your database to. \n \n \n When completed, click on “Get publish profile” and save the file somewhere safe. You will need to import it into Visual Studio later. Azure Traffic Manager profile The Azure Traffic Manager will help automatically route website visitors to the nearest region. It looks at the IP address of visitors to decide which Web App they should be sent to. In the Azure Portal, click “New” and chose to create a Traffic Manager profile : Choose Performance as the routing method - this means traffic will automatically go to the nearest location). When completed, click “Endpoints” and add your Azure Web Apps: The address will be “http://profilename.trafficmanager.net”. If you want to assign a custom domain (“www.yoursite.com”), follow these instructions . Deploying the Web App Now I suggest you download the source code for the web app. You will need Visual Studio 2017 (or equivalent) to build and publish the web app to your Azure accounts. The web application has been developed in Visual Studio using ASP.NET MVC. However, it could easily have been developed using other platforms such as Node.js, Java or Python, since Azure Cosmos DB provides client libraries for multiple platforms. This is what you need to do: \n \n \n Open Visual Studio. \n \n \n \n \n \n Edit Web.config (instructions below!) with your settings, including your Azure Cosmos DB EndpointURL and AuthKey. \n \n \n \n \n \n Optionally: Test run locally from Visual Studio. \n \n \n \n \n \n Import your publish profiles for the web apps. \n \n \n \n \n \n Publish to Azure and test each site. \n \n \n \n \n \n Also, test through your Azure Traffic Manager address (if you have that in place). You can see which real website you have connected to through the Diagnostics page. \n \n \n Here are some screenshots of what you should see: Web.config These are the settings in Web.config that you should review: <add key=\"ConnectionMode\" value=\"Direct\" /> <add key=\"ConnectionProtocol\" value=\"Tcp\" /> <add key=\"InitialThroughput\" value=\"400\" /> <add key=\"MaxConnectionLimit\" value=\"500\" /> <add key=\"DatabaseId\" value=\"Planetzine\" /> <add key=\"ConsistencyLevel\" value=\"Session\" /> <!-- CONFIGURE THESE! --> <add key=\"EndpointURL\" value=\"https://planetzine.documents.azure.com:443/\" /> <add key=\"AuthKey\" value=\"EnterYourSecretKeyHere\" /> <!-- CONFIGURE THESE! --> These configuration parameters are read by the DbHelper class in the web app. \n \n \n The ConnectionMode and ConnectionProtocol are set to Direct/Tcp, which are the fastest options. \n \n \n \n \n \n MaxConnectionLimit sets the maximum number of simultaneous connections to the database. When doing performance test, it is important you set this number high enough. \n \n \n \n \n \n The InitialThroughput is used when the web application is run for the first time, and a new collection is created. Must be minimum 400 RU/s. You can easily adjust the throughput (and costs) at any time through the Azure Portal or programmatically. \n \n \n \n \n \n EndpointURL is the endpoint address of your account. It can be found in the Azure Portal under the Keys tab. It is called “URI” in the Azure Portal. \n \n \n \n \n \n AuthKey is your secret authentication key. It can be found in the Azure Portal under the Keys tab. You can use either the “PRIMARY KEY”, or the “SECONDARY KEY.” \n \n \n The SQL API *Note: The following is already done if you download my source code. To use the Azure Cosmos DB SQL API in your ASP.NET web application, or any .NET application, you need to add a reference to the SDK. In Visual Studio, right-click on “Manage NuGet packages…” and install the Microsoft.Azure.DocumentDB package (note that it is called DocumentDB, due to the API being previously known as DocumentDB API). The SQL API (Microsoft.Azure.DocumentDB) is pretty straightforward to use. Going through the API would be outside of the scope of this article, so I recommend looking at the Azure Cosmos DB: SQL API documentation . Creation of databases and collections Databases and collections are created (if they don’t already exist) every time the web app starts. This is done from Global.asax.cs. If you are using a non-free Azure Cosmos DB account, remember to delete the databases/collections when you are done testing, so you don’t get charged unnecessarily. The DbHelper class *Note: this is information about the DbHelper class, which is also part of my source code. One of the most important classes in my sample web application is the DbHelper class. It handles all communications with the Azure Cosmos DB database. \n \n \n The constructor of the DbHelper class reads all the settings. \n \n \n \n \n \n It then determines the preferred locations (for reading data) from the server’s actual region. \n \n \n \n \n \n It then creates a connection policy and applies the preferred locations to the connection policy. \n \n \n \n \n \n It then creates the client. \n \n \n \n \n \n Finally it calls OpenAsync on the client, to avoid a startup latency on the first request. \n \n \n Note that the DbHelper class is static and that there will never be more than one client. It’s best practice never to use multiple clients to communicate with a single endpoint. Note also that all methods of the DbHelper class are asynchronous. This is also best practice since the SQL API itself is asynchronous, and we should avoid any blocking. The DbHelper class supports the basic operations: creating a database, creating a collection, creating a document, upserting a document (which means that it replaces a document if it already is there, otherwise creates it), reading and querying. The Article class The structure of the Article class looks like this (in shortened form): public class Article { public const string CollectionId = \"articles\"; public const string PartitionKey = \"/partitionId\"; [JsonProperty(\"id\")] public Guid ArticleId; [JsonProperty(\"partitionId\")] public string PartitionId => Author; [JsonProperty(\"heading\")] public string Heading; [JsonProperty(\"imageUrl\")] public string ImageUrl; [JsonProperty(\"body\")] public string Body; [JsonProperty(\"tags\")] public string[] Tags; [JsonProperty(\"visible\")] public bool Visible; [JsonProperty(\"author\")] public string Author; [JsonProperty(\"publishDate\")] [JsonConverter(typeof(IsoDateTimeConverter))] public DateTime PublishDate; [JsonProperty(\"lastUpdate\")] [JsonConverter(typeof(IsoDateTimeConverter))] public DateTime LastUpdate; } \n \n \n Note the attributes I have added to support JSON serialization. \n \n \n \n \n \n Note that I rename my ArticleId to “id”. This is because “id” is the reserved name the SQL API uses for the unique identifier of a document. \n \n \n \n \n \n Note also the partition key. Articles are partitioned by Author. This partition key is chosen because it is a logical way to group articles and will be pretty scalable. \n \n \n Conclusion InfoWorld’s article outlining the “Technology of the Year 2018” writes : “Do you need a distributed NoSQL database with a choice of APIs and consistency models? That would be Microsoft’s Azure Cosmos DB.” Azure Cosmos DB is easy to use. It supports multiple APIs (including a SQL API) and is compatible with MongoDB, Cassandra, and Gremlin. It also comes with client libraries in multiple different programming languages (with 5-minute quickstarts available). Azure Cosmos DB is also useful for pretty much all sizes of applications, from small to planet-scale. You can start small and seamlessly grow data volume, throughput and number of regions. Just be careful about partition keys. The choice of partition key is very important. Typically, good partition keys are customer-ids, user-ids or device-ids. Don’t worry about having too many partitions. As your data grows, it is just beneficial that also the number of partitions grows. Azure Cosmos DB is also a stable database service that comes with comprehensive guarantees (SLAs) of high availability and low latencies. It empowers developers to make precise tradeoffs in latency, throughput, availability, and consistency by offering five well-defined consistency levels. Finally, Microsoft has a feedback website where you can vote for Azure Cosmos DB ideas/features and submit your ideas for voting. Microsoft actively comments on the ideas, and it gives some pretty good hints about what new things to expect in Azure Cosmos DB in the future! References \n \n \n Azure Cosmos DB documentation and quickstarts \n \n \n \n \n \n Azure Cosmos DB FAQ \n \n \n \n \n \n Planetzine source code on GitHub \n \n \n \n \n \n A technical overview of Azure Cosmos DB \n \n \n \n \n \n Partition and scale in Azure Cosmos DB \n \n \n \n \n \n InfoWorld’s 2018 Technology of the Year Award winners \n \n \n \n \n \n Azure Cosmos DB on Twitter \n \n \n \n \n \n My blog posts about Azure Cosmos DB \n \n \n Johan Åhlén is an internationally recognized consultant and Data Platform MVP. He is passionate about innovation and new technologies, and shares this passion through articles, presentations and videos. Johan founded and co-managed PASS SQLRally Nordic, the largest SQLRally conference in the world. He also founded SolidQ in Sweden. Johan built up the Swedish SQL Server Group and served as the president of the user group between 2009-2016. In 2017 he founded the Skåne Azure User Group. He has been recognized by TechWorld/Computer Sweden as one of the top developers in Sweden. 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