Editing Online analytical processing (section)

==== Disadvantages of ROLAP ====
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* There is a consensus in the industry that ROLAP tools have slower performance than MOLAP tools. However, see the discussion below about ROLAP performance.
* The loading of ''aggregate tables'' must be managed by custom [[Extract, transform, load|ETL]] code. The ROLAP tools do not help with this task. This means additional development time and more code to support.
* When the step of creating aggregate tables is skipped, the query performance then suffers because the larger detailed tables must be queried. This can be partially remedied by adding additional aggregate tables; however it is still not practical to create aggregate tables for all combinations of dimensions/attributes.
* ROLAP relies on the general-purpose database for querying and caching, and therefore several special techniques employed by [[MOLAP]] tools are not available (such as special hierarchical indexing). However, modern ROLAP tools take advantage of latest improvements in [[SQL]] language such as CUBE and ROLLUP operators, DB2 Cube Views, as well as other SQL OLAP extensions. These SQL improvements can mitigate the benefits of the [[MOLAP]] tools.
* Since ROLAP tools rely on [[SQL]] for all of the computations, they are not suitable when the model is heavy on calculations which don't translate well into [[SQL]]. Examples of such models include budgeting, allocations, financial reporting and other scenarios.