A data analytics team wishes to perform daily data export from DynamoDB table and an import into an S3 bucket in parquet file format for further data analytics processing. What is the operationally optimal solution?

Answer options:

A.Use AWS Data Pipeline service to manage the Amazon EMR jobs for data export, conversion, and data import.
B.Use AWS Step functions to manage the data export, conversion, and data import workflow.Use AWS Glue job to perform the data export, conversion, and data import.
C.Enable DynamoDB Streams. Create a Lambda function to poll the DynamoDB stream, perform data conversion, and deliver batch records to S3.
D.Enable DynamoDB Streams. Create Lambda function to poll DynamoDB stream and push items to Kinesis Data Firehose. Use Data Firehose to perform data conversion and store the data in S3.

Answer: B
Option A is incorrect because it is not an operationally optimal solution. This option requires provisioning and management of EMR cluster instances to perform the data ETL operations.
Option B is CORRECT because a relatively simple AWS Glue job can be created to perform ETL operations. Glue has the native capability to connect to DynamoDB and S3 for read/write operations.It also contains native support for the parquet data format.Further, this solution is completely serverless, thus requiring less operational overhead.
Option C is incorrect because there are additional costs associated with using DynamoDB Streams.Additionally, more complex code is required to implement data conversion in the Lambda function.Lastly, polling the stream makes this a real-time solution and not a daily batch export as specified in requirements. Thus, this is not the optimal solution.
Option D is incorrect because using DynamoDB streams with Kinesis Data Firehose implements a real-time data streaming solution and not a daily batch export as specified in requirements.Therefore, this is not the correct solution.
Reference:
https://aws.amazon.com/blogs/big-data/how-to-export-an-amazon-dynamodb-table-to-amazon-s3-using-aws-step-functions-and-aws-glue/