GCP Professional Data Engineer Practice Question

An e-commerce retailer stores all order data in an on-premises Oracle 12c database. Analysts need this data available in BigQuery for near-real-time reporting, while the engineering team wants every change captured in Cloud Storage for replay if pipelines fail. The solution must

stream new and updated rows within seconds,
avoid installing agents or creating excessive read locks on the source database, and
automatically propagate future schema changes to the cloud targets. Which Google Cloud service should you choose to implement the data movement with minimal operational overhead?

Database Migration Service with continuous replication from Oracle to Cloud SQL followed by federated queries from BigQuery.
Datastream, to stream Oracle change data capture records into Cloud Storage and automatically ingest them into BigQuery.
BigQuery Data Transfer Service configured with an Oracle connector to load tables on a daily schedule.
A custom Apache Beam pipeline on Dataflow that polls the Oracle database and writes results to BigQuery and Cloud Storage.

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Answer Description

Datastream is Google Cloud's serverless change data capture (CDC) and replication service that connects to Oracle or MySQL sources without requiring agents on the database host. It streams insert, update, and delete events in near real time, writes them to Cloud Storage in Avro/JSON, and can automatically deliver the data into BigQuery while forwarding DDL statements to keep the destination schema in sync. Database Migration Service focuses on moving entire databases to Cloud SQL, not to BigQuery or Cloud Storage. BigQuery Data Transfer Service offers scheduled batch loads from SaaS apps or files, not CDC from Oracle. Building a custom Dataflow pipeline around Oracle redo logs would meet the requirements but imposes significant development and operational burden, conflicting with the "minimal operational overhead" constraint. Therefore, Datastream is the most suitable choice.

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