{"id":78,"date":"2019-11-04T12:04:28","date_gmt":"2019-11-04T20:04:28","guid":{"rendered":"http:\/\/devblogs.microsoft.com\/cosmosdb\/?p=78"},"modified":"2019-12-12T19:28:17","modified_gmt":"2019-12-13T03:28:17","slug":"whats-new-in-azure-cosmos-db-nov-2019","status":"publish","type":"post","link":"https:\/\/devblogs.microsoft.com\/cosmosdb\/whats-new-in-azure-cosmos-db-nov-2019\/","title":{"rendered":"What\u2019s new in Azure Cosmos DB: November 2019"},"content":{"rendered":"

Azure Cosmos DB<\/a> is Microsoft\u2019s globally distributed, multi-model database service. It offers\u00a0turn-key global distribution<\/a>, guarantees\u00a0single-digit millisecond<\/a> latency at the 99th<\/sup>\u00a0percentile, 99.999 percent\u00a0high availability<\/a>, and\u00a0elastic scaling<\/a>\u00a0of\u00a0throughput and storage<\/a>.<\/p>\n

For Ignite 2019, we\u2019re excited to announce tons of new features, capabilities and improvements for our users based on your feedback, including support for GROUP BY queries, automatic scaling of throughput, an analytical storage engine for fast analytical queries, and more.<\/p>\n

GROUP BY support<\/h4>\n

Azure Cosmos DB now supports GROUP BY queries<\/a>! This is one of our top asks from customers and we are excited to release this capability. With GROUP BY, you can run queries that group your results according to the values of one or more specified properties. This feature is currently supported in Data Explorer, JavaScript SDK 3.4<\/a>, and .NET SDK 3.3<\/a>. Support for other SDKs will be available later this year.<\/p>\n

\"Running<\/a><\/p>\n

Autopilot Preview<\/h4>\n

Estimating the right amount of throughput (RU\/s) for your Cosmos databases and containers is key to optimizing cost and performance. We\u2019ve heard from many of our customers that this can be a hard problem.<\/p>\n

We\u2019re excited to announce that we are making this a lot easier with our preview of Autopilot. With Autopilot, Azure Cosmos DB will automatically manage and scale the RU\/s<\/a> of your containers based on the usage. This eliminates the need for custom scripting to change RU\/s and makes it easier to handle bursty, unpredictable workloads.<\/p>\n

You can try out Autopilot in your Cosmos accounts by going to the Azure Portal and enabling the feature in the \u201cPreview Features\u201d blade.<\/p>\n

\"Enable<\/a><\/p>\n

Then, in the container create pane, select Autopilot mode and choose the max RU\/s you want Azure Cosmos DB to scale to.<\/p>\n

\"In<\/a><\/p>\n

Analytical storage & Synapse integration private preview<\/h4>\n

Many of our customers store operational or hot data in Azure Cosmos DB and would like to do analytics on larger volumes of current and historical data. Customers typically use our\u00a0Change Feed<\/a>\u00a0or other ETL mechanisms to move the hot data into storage suitable for analytics and run their analytical queries there.<\/p>\n

With our new analytical storage engine<\/a> and Synapse integration<\/a> preview, this capability is natively built into Azure Cosmos DB. Cosmos containers can now be enabled to be backed by two storage engines: a transactional storage engine \u2013 Azure Cosmos DB as you know it today \u2013 and a new analytical storage engine. For analytical workloads, you can configure your container to automatically have your data encoded in a versioned columnar storage format for fast analytical queries, scans and updates. This data is stored in a cost-efficient off-cluster storage<\/a>, with no ETL from your end required. We’ve also integrated our Azure Cosmos DB Spark connector directly into Azure Synapse Analytics’ Spark capabilities, making it easy to query and operate over your data.<\/p>\n

To sign-up for the private preview, go to your Cosmos account in the Azure Portal and register for the feature in the \u201cPreview Features” blade. You can connect to a Synapse workspace and Spark pool resource directly from a Azure Cosmos DB notebook in Data Explorer.<\/p>\n

\"Enable<\/a><\/p>\n

\"Connect<\/a><\/h4>\n

Built-in Jupyter notebooks updates<\/h4>\n

In September, we made built-in Jupyter notebooks, or Cosmic notebooks<\/a> available. Since then, we’ve added new features, including an %upload magic command that makes it easier and faster to import data, new built-in chart UX with Nteract<\/a> integration, and support for Azure Synapse Analytics<\/a> workspaces.<\/p>\n

Developers, data scientists, engineers and analysts can use these notebooks \u2013 which are directly integrated in the Azure portal \u2013 to interactively run queries, explore, analyze, and visualize their Cosmos data, and build\/train machine learning models. We\u2019ve also bundled in our latest Azure Cosmos DB Python SDK<\/a> and SQL query magic commands<\/a> to make it easier to run operations against your data, no setup required. Get started<\/a> with notebooks and checkout our samples gallery<\/a>.<\/p>\n

\"New<\/a><\/h4>\n

Cosmos Explorer<\/h4>\n

Cosmos Explorer<\/a>, the full-screen standalone web-based version of the Azure Cosmos DB Data Explorer, now supports API for MongoDB<\/a> and Cassandra API<\/a> accounts, in addition to SQL (Core),<\/a> Table<\/a>, and Gremlin<\/a> API. You can use Cosmos Explorer to access your database accounts for all APIs to do common operations, like creating new resources, running queries, and more. You can also share temporary access to authorized peers, without the need for them to have subscription or Azure portal access.<\/p>\n

\"Access<\/a><\/p>\n

Bulk execution mode in .NET SDK<\/h4>\n

With the new bulk execution mode directly in the Cosmos .NET SDK, you no longer need to use a separate Cosmos bulk executor library to use bulk functionality. For bulk import and delete scenarios, you can now use bulk operation mode to optimize your usage of provisioned RU\/s, all with the same SDK for your bulk operations and client application.<\/p>\n

Bulk execution mode is available in Cosmos .NET SDK version 3.4<\/a> and later. It supports point operations (Create, Read, Upsert, Replace, Delete). Using it requires minimal code change: just set the AllowBulkExecution property when initializing your CosmosClient<\/a> and run your point operations as normal. Behind the scenes, the SDK will group concurrent operations into a single service call to optimize the throughput utilization. Get started with our tutorial<\/a>.<\/p>\n

Transactional batch in .NET SDK<\/h4>\n

You can now do a transactional batch of operations on your data with the same partition key value, using the Cosmos .NET SDK version 3.4 and later. Previously you had to author and call server-side stored procedures<\/a> written in JavaScript to achieve the same functionality. Operations in a batch will either all succeed atomically, or all be rolled back together.<\/p>\n