You might want to look into Apache Kafka, with log compaction, which provides a model to accomplish exactly that while also handing message passing/data streami

You might want to look into Apache Kafka, with log compaction, which provides a model to accomplish exactly that while also handing message passing/data streaming. Your data warehouse can suck facts from Kafka (with ETL on either side of the operation, or even integrated into Kafka if you so desire), and you can keep Kafka channels loaded with micro-"Truth"s (current accounts, current employees, etc). That way apps get basically real-time simplified access to the data warehouse while your data warehouse gets a client streaming story that's wicked scalable. And no coupling in between... It's a different approach than some mainstream solutions, but IMO hits a nice goldilocks zone between application and service communication and making data warehousing in parallel realistic and digestible. YMMV, naturally :)