Information AboutRolap |
| CATEGORIES ABOUT ROLAP | |
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Please review the discussion page before making changes to the advantages or disadvantages. Thank you. --> ROLAP stands for Relational '''O'''n'''l'''ine '''A'''nalytical '''P'''rocessing. ROLAP is an alternative to the MOLAP (Multidimensional OLAP ) technology. While both ROLAP and MOLAP analytic tools are designed to allow analysis of data through the use of a Multidimensional Data Model , ROLAP differs significantly in that it does not require the pre-computation and storage of information. Instead, ROLAP tools access the data in a Relational Database and generate SQL queries to calculate information at the appropriate level when an end user requests it. With ROLAP, it is possible to create additional database tables (''summary tables'' or ''aggregations'') which summarize the data at any desired combination of dimensions. While ROLAP uses a relational database source, generally the database must be carefully designed for ROLAP use. A database which was designed for OLTP will not function well as a ROLAP database. Therefore, ROLAP still involves creating an additional copy of the data. However, since it is a database, a variety of technologies can be used to populate the database. ROLAP VS. MOLAP The discussion of the advantages and disadvantages of ROLAP below, focus on those things that are true of the most widely used ROLAP and MOLAP tools available today. In some cases there will be tools which are exceptions to any generalization made. Advantages of ROLAP
Disadvantages of ROLAP
Performance of ROLAP In the OLAP industry ROLAP is usually perceived as being able to scale for large data volumes, but suffering from slower query performance as opposed to MOLAP. The OLAP Survey , the largest independent survey across all major OLAP products, being conducted for 5 years (2001 to 2005) have consistently found that companies using ROLAP report slower performance than those using MOLAP. However, as with any survey there are a number of subtle issues that must be taken into account when interpreting the results. ROLAP tools are generally selected by companies with larger volumes of data (high cardinality dimensions), due to ROLAPs superior scalability, and the same survey also consistently confirms this. Obviously, larger data volumes lead to longer query times. There is also a question about complexity of the model, measured both in number of dimensions and richness of calculations. ROLAP is more often used in the sales and marketing applications since it lacks the support for sophisticated multidimensional calculations, therefore it requires less computations to answer queries. The survey does not offer a good way to control for these variations in the data being analyzed. Some companies select ROLAP because they intend to re-use existing relational database tables -- these tables will frequently not be optimally designed for OLAP use. The superior flexibility of ROLAP tools allows this less than optimal design to work, but performance suffers. MOLAP tools in contrast would force the data to be re-loaded into an optimal OLAP design. Proponents of ROLAP claim that given the same data and the same multi-dimensional design, it is possible to setup a ROLAP system which will perform as well as a MOLAP system. Proponents of MOLAP, on the other side, claim that MOLAP system will always outperform ROLAP at query time due to optimized storage and indexing. TRENDS The undesirable trade-off between additional 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 MOLAP and which portion in ROLAP . PRODUCTS Examples of commercial products using ROLAP include Microsoft Analysis Services , Microstrategy and Business Objects . There is open source ROLAP server - Mondrian. EXTERNAL LINKS
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