
The historical architecture of data management has consistently suffered from a fundamental split where operational systems and analytical engines operate in entirely different technological universes. This persistent friction has compelled organizations to maintain fragile Change Data Capture pipelines that frequently break under the pressure of high-volume transactional updates or complex analytical demands. When these pipelines fail, the resulting data inconsistency










