A large automobile company is migrating the database of a critical financial application to Amazon DynamoDB. The company's risk and compliance policy requires that every change in the database be recorded as a log entry for audits. The system is anticipating more than 500,000 log entries each minute.
Log entries should be stored in batches of at least 100,000 records in each file in Apache Parquet format.
How should a database specialist implement these requirements with DynamoDB?

A. Enable Amazon DynamoDB Streams on the table. Create an AWS Lambda function triggered by the stream. Write the log entries to an Amazon S3 object.
B. Create a backup plan in AWS Backup to back up the DynamoDB table once a day. Create an AWS Lambda function that restores the backup in another table and compares both tables for changes. Generate the log entries and write them to an Amazon S3 object.
C. Enable AWS CloudTrail logs on the table. Create an AWS Lambda function that reads the log files once an hour and filters DynamoDB API actions. Write the filtered log files to Amazon S3.
D. Enable Amazon DynamoDB Streams on the table. Create an AWS Lambda function triggered by the stream. Write the log entries to an Amazon Kinesis Data Firehose delivery stream with buffering and Amazon S3 as the destination.