Which solution will meet these requirements with the LEAST delay between when a new order is processed and when QuickSight can access the new order information?
Use AWS Glue to export the data from Amazon DynamoDB to Amazon S3. Configure QuickSight to access the data in Amazon S3.
Use Amazon Kinesis Data Streams to export the data from Amazon DynamoDB to Amazon S3. Configure QuickSight to access the data in Amazon S3.
Use an API call from QuickSight to access the data that is in Amazon DynamoDB directly.
Use Amazon Kinesis Data Firehose to export the data from Amazon DynamoDB to Amazon S3. Configure QuickSight to access the data in Amazon S3.
Explanations:
AWS Glue is typically used for batch ETL processes, not real-time data transfer. It introduces latency, which does not meet the requirement of near real-time insights.
While Kinesis Data Streams can capture real-time data, it requires additional steps to stream the data into S3, adding extra complexity and delay. QuickSight does not have direct integration with Kinesis Data Streams for real-time dashboarding.
QuickSight does not support direct API calls to access data from DynamoDB. It requires data to be stored in a compatible source, such as Amazon S3 or Redshift.
Kinesis Data Firehose can directly stream data from DynamoDB to S3 with minimal latency. QuickSight integrates seamlessly with S3 for near real-time access, making it the optimal solution.
I chart that the answer is:
Use Amazon Kinesis Data Firehose to export the data from Amazon DynamoDB to Amazon S3. Configure QuickSight to access the data in Amazon S3.