Describe different OLAP Servers.

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 OLAP Servers: 

Logically, OLAP servers present business users with multidimensional data from da warehouses or data marts, without concerns regarding how or where the data are stored However, the physical architecture and implementation of OLAP servers must consider data storage issues. Implementations of a warehouse server for OLAP processing include the following: 

There are three main types of OLAP servers: 

Relational OLAP (ROLAP) servers: 

These are the intermediate servers that stand is between a relational back-end server and client front-end tools. They use, a relational or extended-relational DBMS to store and manage warehouse data, and OLAP middleware to support missing pieces. ROLAP servers include optimization for each DBMS back end, implementation of aggregation navigation logic, and additional tools and services. ROLAP technology tends to have greater scalability than MOLAP technology. The DSS server of Microstrategy, for example, adopts the ROLAP approach.


Multidimensional OLAP (MOLAP) servers: 

These servers support multidimensional data views through array-based multidimensional storage engines. They map multi-dimensional views directly to data cube array structures. The advantage of using a data cube is that it allows fast indexing to precomputed summarized 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 dense and sparse data sets: Denser subcubes are identified and stored as array structures, whereas sparse subcubes employ compression technology for efficient storage utilization.


Hybrid OLAP (HOLAP) servers:

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 allow large volumes of detailed data to be stored in a relational database, while aggregations are kept in a separate MOLAP store. The Microsoft SQ1. Server 2000 supports a hybrid OLAP server. 


Specialized SQL servers: 

To meet the growing demand for OLAP processing in relational databases, some database system vendors implement specialized SQL servers that provide advanced query language and query processing support for SQL queries over star and snowflake schemas in a read-only environment.  

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1. Relational OLAP (ROLAP):

Relational OLAP servers are placed between relational back-end servers and client front-end tools. To store and manage the warehouse data, the relational OLAP uses relational or extended-relational DBMS.

Advantages:

  • ROLAP servers can be easily used with existing RDBMS.
  • ROLAP tools do not use pre-calculated data cubes.
  • ROLAP server offers high scalability.
  • Can handle large amounts of information.

Disadvantages:

  • ROLAP needs high utilization of manpower, software, and hardware resources.
  • Query performance in this model is slow.
  • SQL functionality is constrained.


2. Multidimensional OLAP (MOLAP):

Multidimensional OLAP (MOLAP) supports multidimensional views of data through array-based multidimensional storage engines. The advantage of using a data cube is that it allows fast indexing to pre-computed summarized data. With multidimensional data stores, the storage utilization may be low if the data set is sparse.

Advantages:

  •  Fast information retrieval.
  • Easier to use, therefore MOLAP is suitable for inexperienced users.
  • Suitable for slicing and dicing operations.
  • Capable of performing complex calculations.

Disadvantages:

  • MOLAP is not capable of containing detailed data.
  • The storage utilization may be low if the data set is sparse.
  • It is difficult to change the dimensions without re-aggregating.


3. Hybrid OLAP (HOLAP):

Hybrid OLAP is a mixture of both ROLAP and MOLAP. It offers fast computation of MOLAP and higher scalability of ROLAP. HOLAP server allows the storage of large data volumes of detailed information. HOLAP uses two databases.

1. Aggregated or computed data is stored in a multidimensional OLAP cube

2. Detailed information is stored in a relational database.

Advantages:

  • HOLAP provides the benefits of both MOLAP and ROLAP.
  • It provides quick access at all levels of aggregation.

Disadvantages:

  •  HOLAP architecture is very complicated because it supports both MOLAP and ROLAP servers.
  • There are higher chances of overlapping especially in their functionalities.


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