Editing Online analytical processing (section)

===Hybrid OLAP (HOLAP)===
The undesirable trade-off between additional [[Extract, transform, load|ETL]] cost and slow query performance has ensured that most commercial OLAP tools now use a "Hybrid OLAP" (HOLAP) approach, which allows the model designer to decide which portion of the data will be stored in [[#Multidimensional_OLAP_.28MOLAP.29|MOLAP]] and which portion in ROLAP.

There is no clear agreement across the industry as to what constitutes "Hybrid OLAP", except that a database will divide data between relational and specialized storage.<ref name="ieee_cite">{{cite journal
  | last1 = Bach Pedersen | first1 = Torben
  | last2 = S. Jensen 
  | title = Multidimensional Database Technology
  | journal = Distributed Systems Online
  | volume = 34
  | issue = 12
  | issn = 0018-9162
  | pages = 40–46
  | date = December 2001
  | doi = 10.1109/2.970558
  | first2 = Christian }}
</ref> For example, for some vendors, a HOLAP database will use relational tables to hold the larger quantities of detailed data and use specialized storage for at least some aspects of the smaller quantities of more-aggregate or less-detailed data. HOLAP addresses the shortcomings of [[#Multidimensional_OLAP_.28MOLAP.29|MOLAP]] and [[#Relational_OLAP_.28ROLAP.29|ROLAP]] by combining the capabilities of both approaches. HOLAP tools can utilize both pre-calculated cubes and relational data sources.

==== Vertical partitioning ====
In this mode HOLAP stores ''aggregations'' in [[#Multidimensional_OLAP_.28MOLAP.29|MOLAP]] for fast query performance, and detailed data in [[#Relational_OLAP_.28ROLAP.29|ROLAP]] to optimize time of cube ''processing''.

==== Horizontal partitioning ====
In this mode HOLAP stores some slice of data, usually the more recent one (i.e. sliced by Time dimension) in [[#Multidimensional_OLAP_.28MOLAP.29|MOLAP]] for fast query performance, and older data in [[#Relational_OLAP_.28ROLAP.29|ROLAP]]. Moreover, we can store some dices in [[#Multidimensional_OLAP_.28MOLAP.29|MOLAP]] and others in [[#Relational_OLAP_.28ROLAP.29|ROLAP]], leveraging the fact that in a large cuboid, there will be dense and sparse subregions.<ref>{{cite journal|arxiv=cs/0702143|doi=10.1016/j.ins.2005.09.005 |title=Attribute value reordering for efficient hybrid OLAP |year=2006 |last1=Kaser |first1=Owen |last2=Lemire |first2=Daniel |journal=Information Sciences |volume=176 |issue=16 |pages=2304–2336 }}</ref>

==== Products ====
The first product to provide HOLAP storage was [[Holos (software)|Holos]], but the technology also became available in other commercial products such as [[Microsoft Analysis Services]], [[Oracle OLAP|Oracle Database OLAP Option]], [[MicroStrategy]] and [[SAP AG]] BI Accelerator. The hybrid OLAP approach combines ROLAP and MOLAP technology, benefiting from the greater scalability of ROLAP and the faster computation of MOLAP. For example, a HOLAP server may store large volumes of detailed data in a relational database, while aggregations are kept in a separate MOLAP store. The Microsoft SQL Server 7.0 OLAP Services supports a hybrid OLAP server