Difference between MOLAP, ROLAP and HOLAP in SSAS

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

2. Pros Pros Pros
• Provides maximum • Ability to view the • HOLAP balances the
query performance, data in near real-time. disk space
because all the • Since ROLAP does requirement, as it
required data (a copy not make another only stores the
of the detail data and copy of data as in aggregate data on the
calculated aggregate case of MOLAP, it OLAP server and the
data) are stored in the has less storage detail data remains in
OLAP server itself requirements. This is the relational
and there is no need to very advantageous database. So no
refer to the underlying for large datasets duplicate copy of the
relational database. which are queried detail data is
• All the calculations infrequently such as maintained.
are pre-generated historical data. • Since HOLAP does
when the cube is • In ROLAP mode, the not store detail data
processed and stored detail data is stored on the OLAP server,
locally on the OLAP on the underlying the cube and
server hence even the relational database, so partitions would be
complex calculations, there is no limitation smaller in size than
as a part the query on data size that MOLAP cubes and
result, will be ROLAP can support partitions.
performed quickly. or limited by the data • Performance is better
• MOLAP uses size of relational than ROLAP as in
compression to store database. In nutshell, HOLAP the summary
the data on the OLAP it can even handle data are stored on the
server and so has less huge volumes of data. OLAP server and
storage requirements queries can be
than relational satisfied from this
databases for same summary data.
amount of data. • HOLAP would be
• MOLAP does not optimal in the
need to have a scenario where query
permanent connection response is required
to the underlying and query results are
relational database based on
(only at the time of aggregations on large
processing) as it stores volumes of data.
the detail and
aggregate data in the
OLAP server so the
data can be viewed
even when there is
connection to the
relational database.
Cons Cons Cons
• With MOLAP mode, • Compared to • Query performance
you need frequent MOLAP or HOLAP (response time)
processing to pull the query response is degrades if it has to
refreshed data after generally slower drill through the
last processing because everything is detail data from

3. resulting in drain on stored on relational relational data store,
system resources. database and not in this case HOLAP
• Latency; just after the locally on the OLAP performs very much
processing if there is server. like ROLAP.
any changes in the • A permanent
relational database it connection to the
will not be reflected underlying database
on the OLAP server must be maintained to
unless re-processing is view the cube data.
performed.
• MOLAP stores a copy
of the relational data
at OLAP server and so
requires additional
investment for
storage.
• If the data volume is
high, the cube
processing can take
longer, though you
can use incremental
processing to
overcome this.
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