The discussion centers on the potential benefits and challenges of applying Object-Relational Mapper (ORM) principles to Online Analytical Processing (OLAP) databases, particularly ClickHouse. While transactional ORMs like Prisma and SQLAlchemy have been successful in the Online Transaction Processing (OLTP) realm, their extension to OLAP is fraught with difficulties due to fundamental differences between the two database types, such as data storage methods and query complexity. Moose OLAP, part of the open-source MooseStack, seeks to address these challenges by offering an ORM-like interface specifically tailored for OLAP workloads. This involves creating OLAP-native semantics that reflect the unique characteristics of OLAP databases, such as column-orientation and append-only operations, while borrowing beneficial ORM concepts like schema as code for version control and developer ergonomics. The article argues for a distinct OLAP modeling API, rather than extending existing OLTP ORMs, and emphasizes the need for a developer experience that balances simplicity with access to the full power of OLAP databases. Moose OLAP aims to provide a more developer-friendly experience for managing complex analytical queries and schema migrations, without compromising the capabilities that make OLAP databases valuable.