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Difference between ROLAP, MOLAP, and HOLAP?
Relational OLAP (ROLAP) servers
These are the intermediate servers that stand in among a relational back-end server and client front-end tools. They facilitate a relational or extended-relational DBMS to save and manage warehouse data, and OLAP middleware to provide the missing item.
ROLAP servers involve optimization for each DBMS back end, implementation of aggregation navigation logic, and more tools and services. ROLAP technology tends to have higher scalability than MOLAP technology. The DSS server of Micro strategy, for instance, adopts the ROLAP techniques.
ROLAP systems work generally from the data that resides in a relational database, where the base data and dimension tables are saved as relational tables. This model allows the multidimensional analysis of records.
It is the newest and quickest-growing OLAP technology segment in the industry. This method enables several multidimensional views of two-dimensional relational tables to be generated, preventing structuring record around the desired view.
There are various products in this segment have provided reliable SQL engines to support the complexity of multidimensional analysis. This contains making multiple SQL statements to manage user requests, being 'RDBMS' aware and also being capable of creating the SQL statements depends on the optimizer of the DBMS engine.
Multidimensional OLAP (MOLAP) servers
These servers provide multidimensional views of information through array-based multidimensional storage engines. They design multidimensional views precisely to data cube array structures. The benefit of using a data cube is that it enables quick indexing to pre-computed summarized information.
Some MOLAP servers adopt a two-level storage representation to manage dense and sparse data sets including denser subcubes are recognized and saved as array structures, whereas sparse subcubes employ compression technology for effective storage uses.
The main advantage of MOLAP against a ROLAP is that data are summarized and are saved in an optimized format in a multidimensional cube, rather than in a relational database. In MOLAP model, data are structured into proprietary structure by user’s documenting requirements with the calculations pre-generated on the cubes.
Hybrid OLAP (HOLAP) servers
The hybrid OLAP methods combine ROLAP and MOLAP technology, enhancing the higher scalability of ROLAP and the quicker computation of MOLAP. For instance, a HOLAP server can enable high volumes of detailed information to be stored in a relational database, while aggregations are preserved in a separate MOLAP store. The Microsoft SQL Server 2000 provides a hybrid OLAP server.
Specialized SQL servers − It can meet the increasing demand of OLAP processing in relational databases, some database system vendors execute specialized SQL servers that support advanced query language and query processing support for SQL queries over star and snowflake schemas in a read-only environment.
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