I am designing a solution in which Google Cloud SQL will be used to store all data from the regular functioning of the app(kind of OLTP data). The data is expected to grow o
Another method would be to split the write process to CloudSQL and to Cloud Pub/Sub and then have a Dataflow reader to stream into BigQuery. This works well when you have materially different target schema for your BigQuery tables - which is common when denormalizing your relational data.
The upside is that you can reduce overall latency to say a few seconds; however, the main downside is that if your transactional data is highly mutating you will have to create a versioning scheme to track changes.