Editing Online analytical processing (section)

==== Advantages of ROLAP ====
<!--Note to editors:
Please review the discussion page before making changes to the advantages or disadvantages. Thank you.
-->

* ROLAP is considered to be more scalable in handling large data volumes, especially models with [[Dimension (data warehouse)|dimensions]] with very high [[cardinality]] (i.e., millions of members).
* With a variety of data loading tools available, and the ability to fine-tune the [[extract, transform, load]] (ETL) code to the particular data model, load times are generally much shorter than with the automated [[#Multidimensional_OLAP_.28MOLAP.29|MOLAP]] loads.
* The data are stored in a standard [[relational database]] and can be accessed by any [[SQL]] reporting tool (the tool does not have to be an OLAP tool).
* ROLAP tools are better at handling ''non-aggregable facts'' (e.g., textual descriptions). [[#Multidimensional_OLAP_.28MOLAP.29|MOLAP]] tools tend to suffer from slow performance when querying these elements.
* By [[Decoupling (electronics)|decoupling]] the data storage from the multi-dimensional model, it is possible to successfully model data that would not otherwise fit into a strict dimensional model.
* The ROLAP approach can leverage [[database]] authorization controls such as [[row-level security]], whereby the query results are filtered depending on preset criteria applied, for example, to a given user or group of users ([[SQL]] WHERE clause).