Which approach meets these requirements with MINIMAL effort?
Create a blockchain to store the insurance details. Validate the data using a hash function to verify the data lineage of an insurance claim.
Create an Amazon DynamoDB table to store the insurance details. Validate the data using AWS DMS validation by moving the data to Amazon S3 to verify the data lineage of an insurance claim.
Create an Amazon QLDB ledger to store the insurance details. Validate the data by choosing the ledger name in the digest request to verify the data lineage of an insurance claim.
Create an Amazon Aurora database to store the insurance details. Validate the data using AWS DMS validation by moving the data to Amazon S3 to verify the data lineage of an insurance claim.
Explanations:
Blockchain is an over-engineered solution for this use case. It requires complex implementation and maintenance.
DynamoDB is not ideal for immutable data and tracking historical changes. AWS DMS and S3 are also unnecessary here.
Amazon QLDB is purpose-built for immutable, verifiable data with built-in cryptographic verification of changes.
Amazon Aurora does not inherently support immutability and verifiable history as required by the use case.
In my experience, the answer is:
Create an Amazon QLDB ledger to store the insurance details. Validate the data by choosing the ledger name in the digest request to verify the data lineage of an insurance claim.