Cloud storage systems are a subset, but often also the foundation of cloud computing
systems and therefore share the properties listed above. There are a plethora of
different cloud storage services around and here again it is very hard to give an exact
definition. On one side there are services which enable the end user to store simple
files as a backup solution. On the other hand there are a lot of new database systems
which are commonly called key/value stores. The expression Key/value store is an
umbrella term for services which are often also described as document-oriented,
attribute-oriented, distributed hash table, and key/value database. All of these names
are a variation on the same theme which emphasize different aspects of these systems.
Because of the frequent changes in this field and and due to the fact that every few
weeks a new systems appears on the horizon, we will refer the reader to online lists to
see a comparison of such systems.
One of the key distinction characteristics of cloud storage systems compared to
traditional RDBMS is the different and diametrically opposed emphasis on consistency
and availability. We have already mentioned the CAP-theorem in the introduction. The
older traditional RDBMS are built around the historical basis that consistency is the
main aim to achieve in a database system. As a result they often struggle scaling up
vertically beyond a small number of server nodes. With many servers, the failure rate
increases, and by enforcing consistency the availability decreases.
Cloud storage systems on the other hand are built around the premise to be available
almost constantly and to scale out on a large number of nodes. This is necessary to
serve the needs of highly demanded web services which operate on a worldwide scale.
Yet high availability can only be achieved by cutting back at the consistency guarantee.
Instead of full ACID guarantees as traditional RDBMS most cloud storage systems
support BASE properties. BASE stands for basically available, soft-state and eventual
consistency.
systems and therefore share the properties listed above. There are a plethora of
different cloud storage services around and here again it is very hard to give an exact
definition. On one side there are services which enable the end user to store simple
files as a backup solution. On the other hand there are a lot of new database systems
which are commonly called key/value stores. The expression Key/value store is an
umbrella term for services which are often also described as document-oriented,
attribute-oriented, distributed hash table, and key/value database. All of these names
are a variation on the same theme which emphasize different aspects of these systems.
Because of the frequent changes in this field and and due to the fact that every few
weeks a new systems appears on the horizon, we will refer the reader to online lists to
see a comparison of such systems.
One of the key distinction characteristics of cloud storage systems compared to
traditional RDBMS is the different and diametrically opposed emphasis on consistency
and availability. We have already mentioned the CAP-theorem in the introduction. The
older traditional RDBMS are built around the historical basis that consistency is the
main aim to achieve in a database system. As a result they often struggle scaling up
vertically beyond a small number of server nodes. With many servers, the failure rate
increases, and by enforcing consistency the availability decreases.
Cloud storage systems on the other hand are built around the premise to be available
almost constantly and to scale out on a large number of nodes. This is necessary to
serve the needs of highly demanded web services which operate on a worldwide scale.
Yet high availability can only be achieved by cutting back at the consistency guarantee.
Instead of full ACID guarantees as traditional RDBMS most cloud storage systems
support BASE properties. BASE stands for basically available, soft-state and eventual
consistency.
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