MOLAP

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MOLAP stands for Multidimensional Online Analytical Processing.

MOLAP is an alternative to the ROLAP (Relational OLAP) technology. While both ROLAP and MOLAP analytic tools are designed to allow analysis of data through the use of a multidimensional data model, MOLAP differs significantly in that it requires the pre-computation and storage of information in the cube - the operation known as processing. MOLAP stores this data in an optimized multi-dimensional array storage, rather than in a relational database (i.e. in ROLAP).

1 MOLAP vs. ROLAP
- 1.1 Advantages of MOLAP
- 1.2 Disadvantages of MOLAP
2 Trends
3 Products
4 External links

[edit] MOLAP vs. ROLAP

[edit] Advantages of MOLAP

Fast query performance due to optimized storage, multidimensional indexing and caching.
Smaller on-disk size of data compared to data stored in relational database due to compression techniques.
Automated computation of higher level aggregates of the data.
It is very compact for low dimension data sets.
Array model provides natural indexing
Effective data extract achieved through the pre-structuring of aggregated data.

[edit] Disadvantages of MOLAP

The processing step (data load) can be quite lengthy, especially on large data volumes. This is usually remedied by doing only incremental processing, i.e., processing only the data which has changed (usually new data) instead of reprocessing the entire data set.
MOLAP tools traditionally have difficulty querying models with dimensions with very high cardinality (i.e., millions of members).
Certain MOLAP tools (e.g., Essbase) have difficulty updating and querying models with more than ten dimensions. This limit differs depending on the complexity and cardinality of the dimensions in question. It also depends on the number of facts or measures stored. Other MOLAP tools (e.g., Microsoft Analysis Services or Applix TM1) can handle hundreds of dimensions.
MOLAP approach introduces data redundancy.

[edit] Trends

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.

[edit] Products

Examples of commercial products that use MOLAP are Cognos Powerplay, Oracle OLAP, Microsoft Analysis Services, Essbase, MIS Alea and TM1. There is also an open source MOLAP server Palo.