Azure Stream Analytics: Best Input Options for High Throughput and Low Latencies

Azure Stream Analytics Input Options

Question

While working on one of your company's projects, your teammate wants to check the options for input to an Azure Stream Analytics task that needs high throughput and low latencies.

He is confused about the input that he should use in this case.

He approaches you and asks you to help him.

Which of the following Azure product would you suggest to him?

Answers

Explanations

Click on the arrows to vote for the correct answer

A. B. C. D. E.

Correct Answer: D

Azure Event Hub is considered as a highly scalable event ingestion service that can take and process over million events within a second.

You can transform and store the data that is sent to the event hubs with the help of storage/batching adapters or real-time analytics provider.

Event Hubs are known for consuming the data streams from applications with high throughput and low latencies.

Option A is incorrect.

Azure table storage is a NoSQL store that is used for schemaless storage of structured data.

Option B is incorrect.

Azure Blob Storage should be used when you desire your application to support streaming and random-access scenarios.

Option C is incorrect.

Azure Queue Storage is used to allow asynchronous message queueing among application components.

Option D is correct.

In the given scenario, You should suggest Azure Event Hubs to your teammate as Event Hubs are the primary choice for consuming the data streams from applications with high throughput and low latencies.

Option E is incorrect.

Azure IoT Hub offers a cloud-hosted solution back end for connecting any device virtually.

To know more about Azure Event Hubs, please visit the below-given link:

If your teammate needs to process high-throughput, low-latency data streams, the ideal Azure product for this purpose would be Azure Event Hubs (option D). Azure Event Hubs is a fully managed, highly scalable data streaming platform that can process millions of events per second with low latency.

Azure Table Storage (option A) is a NoSQL key-value storage service that can be used to store large amounts of structured data. While it can handle high volumes of data, it is not optimized for streaming data processing and may not be suitable for high-throughput, low-latency requirements.

Azure Blob Storage (option B) is a service that provides highly scalable, unstructured object storage for data objects such as text and binary data. While it can handle large volumes of data, it is not optimized for real-time streaming data processing and may not be suitable for high-throughput, low-latency requirements.

Azure Queue Storage (option C) is a service for storing and retrieving messages using a queue model. While it can handle large volumes of messages, it is not optimized for real-time streaming data processing and may not be suitable for high-throughput, low-latency requirements.

Azure IoT Hub (option E) is a fully managed service that enables secure and reliable bi-directional communication between IoT devices and the cloud. While it can handle large volumes of data, it is designed for IoT scenarios and may not be suitable for general-purpose streaming data processing.

In summary, if your teammate needs to process high-throughput, low-latency data streams, Azure Event Hubs would be the best choice among the options provided.