Building, updating, maintaining, and enhancing MOLAP cubes can be difficult. Things such as the time it takes to build a cube, limited dimensionality, limited history, and limited detail all are major issues associated with MOLAP cubes. Teradata has an alternative to alleviate these issues. Defining your cubes as ROLAP will enable a scalable cube solution that will result in cubes that are larger in dimensionality, detail, and history that are built in a fraction of the time it took to build a MOLAP cube.

Currently, data warehouses are predominantly built using RDBMSs. If you have a warehouse built on a relational database, and you want to perform OLAP analysis against it, ROLAP is a natural fit.

Read this white paper to learn how to build and implement ROLAP cubes using Teradata Database AJIs.