Think about the use-case where you want all your Relational data to be denormalised and written to a S3 bucket and then loaded into something like Redshift for

Think about the use-case where you want all your Relational data to be denormalised and written to a S3 bucket and then loaded into something like Redshift for analytical loads. If you start pushing the data from your application itself then you introduce the problem of dual-writes (what if S3 write failed? what if RDBMS failed?). If instead you treat your RDBMS as the source of truth and use something like PostgresSQL's logical decoding feature to listen to the replication stream and then push the events from that stream to S3 you can achieve guaranteed-eventual-consistency. The best way would've obviously been to make your application write to a Message Bus (Kafka etc.) and then some other application would persist that message to your RDBMS. This approach requires more development effort and introduces all the issues that distributed systems face: Read your writes, read follow writes, write follow reads etc.