NoSQL database systems have gained significant traction in the OLTP domain due to their scalability, availability, and support for agile development, primarily through a flexible document model that allows for quick schema adaptations. This flexibility enables developers to bypass traditional database administrative hurdles, facilitating rapid application evolution. However, the integration of NoSQL databases with downstream analytical systems, which largely rely on relational models, presents challenges, especially in converting flexible schemas into fixed relational formats. Despite these challenges, enterprises have continued to use relational databases for analytics due to their support for complex queries through Massive Parallel Processing, column-oriented storage, cost-based query optimization, and horizontal scalability, which are essential for efficient analytics. Capella Columnar, a NoSQL document-oriented database cloud service, addresses these analytics needs by combining a flexible document model with storage-compute separation and cost-based optimization, significantly reducing ETL efforts and synchronizing analytical applications with real-time data from upstream OLTP systems.