Difference between MOLAP, ROLAP and HOLAP in SSAS
MOLAP |
ROLAP
|
HOLAP
|
MOLAP
stands for Multidimensional Online Analytical Processing
|
ROLAP
stands for Relational
Online Analytical Processing
|
HOLAP
stands for Hybrid Online
Analytical Processing
|
The MOLAP storage mode causes the aggregations of the partition and a copy of its source data to be stored in a multidimensional structure in Analysis Services when the partition is processed. |
The
ROLAP storage mode causes the aggregations of the partition to be
stored in indexed views in the relational database that was
specified in the partition’s data source.
|
The
HOLAP storage mode combines attributes of both MOLAP and ROLAP.
Like MOLAP, HOLAP causes the aggregations of the partition to be
stored in a multidimensional structure in an SQL Server Analysis
Services instance.
|
This MOLAP structure is highly optimized to maximize query performance. The storage location can be on the computer where the partition is defined or on another computer running Analysis Services. Because a copy of the source data resides in the multidimensional structure, queries can be resolved without accessing the partition’s source data. |
Unlike
the MOLAP storage mode, ROLAP does not cause a copy of the source
data to be stored in the Analysis Services data folders. Instead,
when results cannot be derived from the query cache, the indexed
views in the data source are accessed to answer queries.
|
HOLAP
does not cause a copy of the source data to be stored. For queries
that access only summary data in the aggregations of a partition,
HOLAP is the equivalent of MOLAP.
|
Query response times can be decreased substantially by using aggregations. The data in the partition’s MOLAP structure is only as current as the most recent processing of the partition. |
Query
response is generally slower with ROLAP storage than with the
MOLAP or HOLAP storage modes. Processing time is also typically
slower with ROLAP. However, ROLAP enables users to view data in
real time and can save storage space when you are working with
large datasets that are infrequently queried, such as purely
historical data.
|
Queries
that access source data—for example, if you want to drill down
to an atomic cube cell for which there is no aggregation data—must
retrieve data from the relational database and will not be as fast
as they would be if the source data were stored in the MOLAP
structure. With HOLAP storage mode, users will typically
experience substantial differences in query times depending upon
whether the query can be resolved from cache or aggregations
versus from the source data itself.
|
Pros
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Pros
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Pros
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Cons
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Cons
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Cons
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