Stream Analytics Job Input Options
Question
You are leading an IT team in Azure company and a new member joined the team.
He reviews the options for an input to an Azure Stream Analytics job that your IT team is working on (which requires high throughput and low latency)
He seems confused about input he should use and therefore asks you “Which Azure product should I plan to use for the job's input?” What would be your answer?
Answers
Explanations
Click on the arrows to vote for the correct answer
A. B. C. D. E.Correct Answer: C
Azure Event Hubs are the Azure product that consumes data streams from applications at high throughput and low latency.
The following diagram demonstrates how data is sent to Azure Stream Analytics, analyzed, and sent for further actions like presentation or storage.
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Option A is incorrect.
Using Azure Table storage for job's input is not the right option.
Option B is incorrect.
Azure Blob Storage is not a recommended choice for high throughput and low latencies.
Azure event hub is a better choice.
Option C is correct.
Azure Event Hubs are the Azure product that consumes data streams from applications at high throughput and low latency.
Option D is incorrect.
Using Azure Data Lake storage for job's input is not the right option.
Option E is incorrect.
Using Azure Queue storage for job's input is not the right option.
To know more about Azure Event hubs, please visit the below-given link:
Based on the requirements of high throughput and low latency for the input to the Azure Stream Analytics job, the most appropriate option among the given choices would be Azure Event Hubs.
Azure Event Hubs is a highly scalable data streaming platform that enables the collection and processing of large amounts of data from various sources in real-time. It can handle millions of events per second with low latency and high throughput, making it a suitable option for the given requirements of the job. It also integrates seamlessly with Azure Stream Analytics, enabling real-time analytics and insights on the collected data.
Azure Table Storage and Azure Blob Storage are object storage services that offer high scalability, durability, and availability for unstructured data. However, they may not be suitable for the given requirements of the job, as they are not designed for real-time data streaming and may not provide the required low latency.
Azure Data Lake Storage is a cloud-based data lake that enables the storage and processing of large amounts of structured and unstructured data at scale. While it provides high throughput and low latency for data processing, it may not be the most suitable option for data input to an Azure Stream Analytics job, as it is not designed for real-time data streaming.
Azure Queue Storage is a service that enables the storage and retrieval of large numbers of messages from a queue. While it can handle high message throughput, it may not be the most suitable option for the given requirements of the job, as it may not provide the required low latency for real-time data processing.
Therefore, based on the given requirements, the most appropriate option for the input to an Azure Stream Analytics job would be Azure Event Hubs.