What
Are The Types of OLAP Systems?
OLAP systems vary
quite a lot, and they have generally been distinguished by a letter tagged onto
the front of the word OLAP. ROLAP and MOLAP are the big players, and the other
distinctions represent little more than the marketing programs on the part of
the vendors to distinguish themselves, for example, SOLAP and DOLAP. Here, we
aim to give you a hint as to what these distinctions mean.
Major OLAP Technology Types:
Relational OLAP (ROLAP) –Star Schema based
Considered the fastest growing OLAP technology style, ROLAP or
“Relational” OLAP systems work primarily from the data that resides in a
relational database, where the base data and dimension tables are stored as
relational tables. This model permits multidimensional analysis of data as this
enables users to perform a function equivalent to that of the traditional OLAP
slicing and dicing feature. This is achieved thorough use of any SQL reporting
tool to extract or ‘query’ data directly from the data warehouse. Wherein
specifying a ‘Where clause’ equals performing a certain slice and dice action.
One advantage of ROLAP over the other styles of OLAP analytic
tools is that it is deemed to be more scalable in handling huge amounts of
data. ROLAP sits on top of relational databases therefore enabling it to
leverage several functionalities that a relational database is capable of.
Another gain of a ROLAP tool is that it is efficient in managing both numeric
and textual data. It also permits users to “drill down” to the leaf details or
the lowest level of a hierarchy structure. However, ROLAP applications display
a slower performance as compared to other style of OLAP tools since,
oftentimes, calculations are performed inside the server. Another demerit of a
ROLAP tool is that as it is dependent on use of SQL for data manipulation, it
may not be ideal for performance of some calculations that are not easily
translatable into an SQL query.
Multidimensional OLAP (MOLAP) –Cube based
Multidimensional OLAP, with a popular acronym of MOLAP, is
widely regarded as the classic form of OLAP. One of the major distinctions of
MOLAP against a ROLAP tool is that data are pre-summarized and are stored in an
optimized format in a multidimensional cube, instead of in a relational
database. In this type of model, data are structured into proprietary formats
in accordance with a client’s reporting requirements with the calculations
pre-generated on the cubes.
This is probably by far, the best OLAP tool to use in making
analysis reports since this enables users to easily reorganize or rotate the
cube structure to view different aspects of data. This is done by way of
slicing and dicing. MOLAP analytic tool are also capable of performing complex
calculations. Since calculations are predefined upon cube creation, this
results in the faster return of computed data. MOLAP systems also provide users
the ability to quickly write back data into a data set. Moreover, in comparison
to ROLAP, MOLAP is considerably less heavy on hardware due to compression
techniques. In a nutshell, MOLAP is more optimized for fast query performance
and retrieval of summarized information.
There are certain limitations to implementation of a MOLAP
system, one primary weakness of which is that MOLAP tool is less scalable than
a ROLAP tool as the former is capable of handling only a limited amount of
data. The MOLAP approach also introduces data redundancy. There are also
certain MOLAP products that encounter difficulty in updating models with
dimensions with very high cardinality.
Hybrid OLAP (HOLAP)
HOLAP is the product of the attempt to incorporate the best
features of MOLAP and ROLAP into a single architecture. This tool tried to
bridge the technology gap of both products by enabling access or use to both
multidimensional database (MDDB) and Relational Database Management System
(RDBMS) data stores. HOLAP systems stores larger quantities of detailed data in
the relational tables while the aggregations are stored in the pre-calculated
cubes. HOLAP also has the capacity to “drill through” from the cube down to the
relational tables for delineated data.Some of the advantages of this system are
better scalability, quick data processing and flexibility in accessing of data
sources.
Other Types:
There are also less popular types of OLAP styles upon which one
could stumble upon every so often. We have listed some of the less famous types
existing in the OLAP industry.
Web OLAP (WOLAP)
Simply put, a Web OLAP which is likewise referred to as Web-enabled
OLAP, pertains to OLAP application which is accessible via the web browser.
Unlike traditional client/server OLAP applications, WOLAP is considered to have
a three-tiered architecture which consists of three components: a client, a
middleware and a database server. Probably some of the most appealing features
of this style of OLAP are the considerably lower investment involved, enhanced
accessibility as a user only needs an internet connection and a web browser to
connect to the data and ease in installation, configuration and deployment
process. But despite all of its unique features, it could still not compare to
a conventional client/server machine. Currently, it is inferior in comparison
to OLAP applications which involve deployment in client machines in terms of
functionality, visual appeal and performance.
Desktop OLAP (DOLAP)
Desktop OLAP, or “DOLAP” is based on the idea that a user can
download a section of the data from the database or source, and work with that
dataset locally, or on their desktop. DOLAP is easier to deploy and has a
cheaper cost but comes with a very limited functionality in comparison with
other OLAP applications.
Mobile OLAP
Mobile OLAP is merely refers to OLAP functionalities on a
wireless or mobile device. This enables users to access and work on OLAP data
and applications remotely thorough the use of their mobile devices.
Spatial OLAP (SOLAP)
With the aim of integrating the capabilities of both Geographic
Information Systems (GIS) and OLAP into a single user interface, “SOLAP” or
Spatial OLAP emerged. SOLAP is created to facilitate management of both spatial
and non-spatial data, as data could come not only in an alphanumeric form, but
also in images and vectors. This technology provides easy and quick exploration
of data that resides on a spatial database. Other different blends of an OLAP
product like the less popular ‘DOLAP’ and ‘ROLAP’ which stands for Database
OLAP and Remote OLAP, ‘LOLAP’ for Local OLAP and ‘RTOLAP’ for Real-Time OLAP
are existing but have barely made a noise on the OLAP industry.
