Database Reference
In-Depth Information
Load and Tenant Balancing
: They must be able to automatically move load
between servers so that most of the hardware resources are effectively utilized
and to avoid any resource overloading situations.
Fault Tolerance
: For transactional workloads, a fault tolerant cloud data manage-
ment system needs to be able to recover from a failure without losing any data or
updates from recently committed transactions. Moreover, it needs to successfully
commit transactions and make progress on a workload even in the face of worker
node failures. For analytical workloads, a fault tolerant cloud data management
system should not need to restart a query if one of the nodes involved in query
processing fails.
Ability to run in a heterogeneous environment
: On cloud computing platforms,
there is a strong trend towards increasing the number of nodes that participate in
query execution. It is nearly impossible to get homogeneous performance across
hundreds or thousands of compute nodes. Part failures that do not cause complete
node failure, but result in degraded hardware performance become more common
at scale. A cloud data management system should be designed to run in a
heterogeneous environment and must take appropriate measures to prevent
performance degrading due to parallel processing on distributed nodes.
However, deploying data-intensive applications on cloud environment is not a
trivial or straightforward task. Armbrust et al. [
68
] and Abadi [
56
] argued a list of
obstacles to the growth of cloud computing applications as follows.
Availability of a Service
: In principle, a distributed system is a system that
operates robustly over a wide network. A particular feature of network com-
puting is that the network links can potentially disappear. Organizations worry
about whether cloud computing services will have adequate availability. High
availability is one of the most challenging goals because even the slightest outage
can have significant financial consequences and impacts customer trust.
Data Confidentiality
: In general, moving data off premises increases the number
of potential security risks and appropriate precautions must be made. Transac-
tional databases typically contain the complete set of operational data needed to
power mission-critical business processes. This data includes detail at the lowest
granularity, and often includes sensitive information such as customer data or
credit card numbers. Therefore, unless such sensitive data is encrypted using a
key that is not located at the host, the data may be accessed by a third party
without the customer's knowledge.
Data Lock-In
: APIs for cloud computing have not been, yet, subject of active
standardization. Thus, customers cannot easily extract their data and programs
from one site to run on another. The concerns about the difficulties of extracting
data from the cloud is preventing some organizations from adopting cloud
computing. Customer lock-in may be attractive to cloud computing providers but
cloud computing users are vulnerable to price increases, to reliability problems,
or even to providers going out of business.
