Which storage solution should you implement for each data stream type?

DRAG DROP
You plan to deploy a storage solution to store the output of stream analytics.
You plan to store the data for the following three types of data streams:
Unstructured JSON data
Exploratory analytics Pictures
You need to implement a storage solution for the data stream types.
Which storage solution should you implement for each data stream type? To answer, drag the appropriate storage solutions to the correct data stream types.
Each storage solution may be used once, more than once, or not at all. You may need to drag the split bar between the panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Select and Place:

Correct Answer:

Explanation/Reference:
Explanation:
Box 1: Azure Data Lake Store
Stream Analytics supports Azure Data Lake Store. Azure Data Lake Store is an enterprise-wide hyper-scale repository for big data analytic workloads. Data Lake Store enables you to store data of any size, type and ingestion speed for operational and exploratory analytics. Stream Analytics has to be authorized to access the Data Lake Store.
Box 2: Azure Cosmos DB
Stream Analytics can target Azure Cosmos DB for JSON output, enabling data archiving and low-latency queries on unstructured JSON data.
Box 3: Azure Blob Storage
Blob storage offers a cost-effective and scalable solution for storing large amounts of unstructured data in the cloud.
Incorrect Asnwers:
Azure SQL Database:
Azure SQL Database can be used as an output for data that is relational in nature or for applications that depend on content being hosted in a relational database.
Stream Analytics jobs write to an existing table in an Azure SQL Database.
Azure Service Bus Queue:
Service Bus Queues offer a First In, First Out (FIFO) message delivery to one or more competing consumers. Typically, messages are expected to be received and processed by the receivers in the temporal order in which they were added to the queue, and each message is received and processed by only one message consumer.
Azure Table Storage
Azure Table storage offers highly available, massively scalable storage, so that an application can automatically scale to meet user demand. Table storage is Microsoft’s NoSQL key/attribute store, which one can leverage for structured data with fewer constraints on the schema. Azure Table storage can be used to store data for persistence and efficient retrieval.
References: https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-define-outputs