“What kinds of OLAP servers exist?” OLAP servers present business users with multidimensional data from data warehouse or data marts, without concerns regarding how or where the data are stored. However, the physical architecture implementation OLAP servers must consider data storage issues. Implementation of a warehouse for OLAP processing includes the following.
Relational OLAP Server
There are the intermediate servers that stand in between a relational back-end server and client front-end tools. They use a relational or extended DBMS to store and manage warehouse data, and OLAP middleware to support missing pieces. ROLAP servers include optimization for each DBMS back end, implementation aggregation navigation logic, and additional tools and services. ROLAP technology tends to have greater scalability than MOLAP technology.
Multidimensional OLAP Servers
These servers support multidimensional views of data through array-based multidimensional storage engines. They map multidimensional views directly to data cube array structure. The advantage of using a data cube is, it allows for indexing to pre computed summarizes data. Notice that with multidimensional data stores, the storage utilization may be low if the data set is sparse. In such cases, sparse matrix compression techniques should be explored.
Many MOLAP servers adopt a two level storage representation to handle sparse and dense data sets: the dense sub cubes are identified and stored as array structures, while the sparse sub cubes employ compression technology for efficient data storage utilization.
The hybrid OLAP approach combines ROLAP and MOLAP technology, benefiting from the greater scalability of ROLAP and faster computation. For example, a HOLAP server may allow large volume of detail data to be stored in a relational database, while aggregations are kept in separate MOLAP store.
Specialized SQL servers
To meet the growing demand of OLAP processing in the relational databases, some relational and data warehousing firms implement specialized SQL servers that provide advance query language and query processing support for SQL queries over star and snowflake schemas in read only environment.
“So how data are actually stored in ROLAP and MOLAP architecture?” As its name implies, ROLAP uses relational tables to store data for online analytical processing. And in MOLAP data is stored in cubic form.
SAP is software organization that is using OLAP servers to develop its intelligent software. Because of this technology data mining and web mining is possible. Three dimensional reports are generated that are very helpful for management to dish up their decisions. These software are far more reliable and intelligent than the software that were in the days gone.