3. DBMS as a Cloud Service
Most DBMS or database management systems are simply software packages that users
can acquire to create, maintain or use a database. However, since the introduction of
cloud computing, DBMS has morphed into an entirely new type of service with its own
unique benefits and task specific advantages. For one thing, any type of cloud service
model will have to employ a dedicated cloud DBMS in order to truly provide customers
with excellent access to data and databases. Traditional DBMS’s are simply not set up or
equipped to deal with the demands of cloud computing. And of course, if DBMS was
deployed as a service as part of a larger package provided, it would likely be much more
efficient in its duties and therefore cheaper in the long run.
The concept of the DBMS has been around since the beginning of commercial
computing; such as the navigational DBMS of the1960’s. Database management systems
are one of the oldest integral components of computing, essentially making it possible to
scan, retrieve and organize data on hard drives and networks. All DBMS, despite whether
traditional or cloud-based, are essentially communicators that function as middlemen
between the operating system and the database.
How is a cloud DBMS different a traditional one? For one thing, cloud-based DBMS
are extremely scalable. They are able to handle volumes of data and processes that would
exhaust a typical DBMS. Despite their scalability however, cloud DBMS are still
somewhat lacking in their ability to scale up to extremely large processes; this is expected
to be remedied in the coming months and years however. Currently, the use of cloud
DBMS’s are principally used in the testing and development of new cloud applications
and processes. But while a stand-alone DBMS can be used on a cloud infrastructure;
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most are not designed to take full advantage of cloud resources. DBMS as a cloud
service-type models seek to capitalize on the disparity between antiquated DBMS models
and their lack of full cloud functionality.
Cloud DBMS may utilize all of these components or may have devised new strategies
that combine one or more elements (like combining data structures and the data query
language, for example). Many organizations are exploring the option of utilizing preexisting
modeling languages as a basis for expansion in a cloud model. This strategy
ultimately saves on the time spent developing cloud DBMS’s as well as enhances their
overall effectiveness, since traditional modeling languages are more than adequate for
handling data.
Despite the benefits offered by cloud-based DBMS, many people still have
apprehensions about them. This is most likely due to the various security issues that have
yet to be dealt with. These security issues stem from the fact that cloud DBMS are hard
to monitor since they often span across multiple hardware stacks and/or servers. Security
becomes a serious issue with cloud DBMS when there’s multiple Virtual Machines
(which might be accessing databases via any number of applications) that might be able to
access a database without being noticed or setting off any alerts. In this type of situation a
malicious person could potentially access pertinent data or cause serious harm to the
integral structure of a database, putting the entire system in jeopardy.
There is however a proposed method for dealing with these types of incongruence. An
obvious solution is the deployment of an autonomous network agent, which rigorously
monitor and defends all activities related to database access. The limitation of this
method however, is that a network agent may be unable to handle extremely large and
dense volumes of activity / traffic.
Arguably, the best solution for dealing with security issues is to employ continuous
database auditing. This involves setting up a system that meticulously records, analyze
and report on all activities regarding database access, especially suspicious database
access. All information regarding these activities is logged and stored in an extremely
remote and secure location with alerts being sent out to cloud management (or including
any other individuals they might have designated to receive this information) in the event
of a breach. This will provide those in charge of security with the information necessary
to determine who is responsible, where they are located as well as the specifics of their
machine / hardware.
While deployment of a dedicated and thorough cloud DBMS hasn’t occurred yet, it is
certainly under development. The emergence of a comprehensive solution for all cloud
service models regarding database management will open the door to a new era of cloud
computing.
Many of these cloud databases are designed to run on a cluster of hundreds to
thousands of nodes, and are capable of serving data ranging from hundreds of terabytes to
petabytes. Compared with traditional relational database servers, such cloud databases
may offer less querying capability and often weaker consistency guarantees, but scale
much better by providing built-in support on availability, elasticity, and load balancing.
On the other hand, data management tools are an important part of relational and
analytical data management business since business analysts are often not technically
advanced and do not feel comfortable interfacing with low-level database software
directly. These tools typically interface with the database using ODBC or JDBC, so
database software that want to work these products must accept SQL queries. Therefore, a
novel technology to combine DBMS capability with Cloud scale scalability is highly
desirable.