You are planning an Azure IoT Hub solution that will include 50,000 IoT devices.
Each device will stream data, including temperature, device ID, and time data. Approximately 50,000 records will be written every second. The data will be visualized in near real time.
You need to recommend a service to store and query the data.
Which two services can you recommend? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Click on the arrows to vote for the correct answer
A. B. C. D.CD
D: Time Series Insights is a fully managed service for time series data. In this architecture, Time Series Insights performs the roles of stream processing, data store, and analytics and reporting. It accepts streaming data from either IoT Hub or Event Hubs and stores, processes, analyzes, and displays the data in near real time.
C: The processed data is stored in an analytical data store, such as Azure Data Explorer, HBase, Azure Cosmos DB, Azure Data Lake, or Blob Storage.
https://docs.microsoft.com/en-us/azure/architecture/data-guide/scenarios/time-seriesFor this scenario, we need to recommend a storage and query service that can handle large volumes of data generated by 50,000 IoT devices streaming data every second. Additionally, the data needs to be visualized in near real-time, which means that we need a solution that can handle fast querying and visualization.
Option A: Azure Table Storage Azure Table Storage is a NoSQL key-value store that can be used to store large volumes of structured data. It is a good option for scenarios where data is not frequently updated and where simple querying is required. However, for this scenario, where 50,000 records will be written every second, Azure Table Storage may not be the best choice.
Option B: Azure Event Grid Azure Event Grid is an eventing service that can be used to manage and route events between different Azure services and custom endpoints. While it can handle large volumes of events, it is not a storage or querying service.
Option C: Azure Cosmos DB SQL API Azure Cosmos DB is a globally distributed, multi-model database service that can handle large volumes of structured and unstructured data. It supports multiple APIs, including SQL, MongoDB, Cassandra, Gremlin, and Azure Table Storage. For this scenario, the SQL API can be used to store and query the data. It provides fast querying and indexing capabilities and can handle the high volume of data generated by the IoT devices.
Option D: Azure Time Series Insights Azure Time Series Insights is a fully managed analytics, storage, and visualization service for managing time-series data. It is designed for scenarios where you need to analyze and visualize large volumes of time-series data in near real-time. For this scenario, Azure Time Series Insights can be used to visualize the data generated by the IoT devices.
Therefore, the recommended services for this scenario are Azure Cosmos DB SQL API and Azure Time Series Insights.