There are three
standard storage modes in OLAP applications
1.
MOLAP
2.
ROLAP
3.
HOLAP
MOLAP
MOLAP (Multi dimensional Online
Analytical Processing) : MOLAP is the most used storage type. Its designed to
offer maximum query performance to the users. the data and aggregations are
stored in a multidimensional format, compressed and optimized for performance.
This is both good and bad. When a cube with MOLAP storage is processed, the
data is pulled from the relational database, the aggregations are performed,
and the data is stored in the AS database. The data inside the cube will
refresh only when the cube is processed, so latency is high.
Advantages:
·
Since the data is stored on the OLAP server in
optimized format, queries (even complex calculations) are faster than ROLAP.
·
The data is compressed so it takes up less
space.
·
And because the data is stored on the OLAP
server, you don’t need to keep the connection to the relational database.
·
Cube browsing is fastest using MOLAP.
ROLAP
ROLAP (Relational Online
Analytical Processing) : ROLAP does not have the high latency disadvantage of
MOLAP. With ROLAP, the data and aggregations are stored in relational format.
This means that there will be zero latency between the relational source
database and the cube.
Disadvantage of this mode is the performance, this type
gives the poorest query performance because no objects benefit from multi
dimensional storage.
Advantages:
·
Since the data is kept in the relational
database instead of on the OLAP server, you can view the data in almost real
time.
·
Also, since the data is kept in the relational
database, it allows for much larger amounts of data, which can mean better
scalability.
·
Low latency.
HOLAP
Hybrid Online Analytical
Processing (HOLAP): HOLAP is a combination of MOLAP and ROLAP. HOLAP stores the
detail data in the relational database but stores the aggregations in
multidimensional format. Because of this, the aggregations will need to be
processed when changes are occur. With HOLAP you kind of have medium query
performance: not as slow as ROLAP, but not as fast as MOLAP. If, however, you
were only querying aggregated data or using a cached query, query performance
would be similar to MOLAP. But when you need to get that detail data,
performance is closer to ROLAP.
Advantages:
·
HOLAP is best used when large amounts of
aggregations are queried often with little detail data, offering high
performance and lower storage requirements.
·
Cubes are smaller than MOLAP since the detail
data is kept in the relational database.
·
Processing time is less than MOLAP since only
aggregations are stored in multidimensional format.
·
Low latency since processing takes place when
changes occur and detail data is kept in the relational database.
