Database Architecture

Data is stored in one location, this location is most often a central computer or database system.
System may contain several processors
Example: Cloud computing/Data farms/Data centres

Pros:

Data integrity is maximized and data redundancy is minimized. This aids in the maintaining of data as accurate and as consistent as possible and enhances data reliability.
Data kept in the same location is easier to be changed, re-organized, mirrored, or analyzed.

Cons:

Highly dependent on network connectivity, the slower the internet connection is , the longer the database access time will be
Bottlenecks can occur as a result of high traffic
No data redundancy makes it very hard to retrieve the data that is unexpectedly lost

Data is distributed across several nodes
It may be stored in multiple computers, located in the same physical location; or may be dispersed over a network of interconnected computers.
The nodes are connected by communication network
System provides necessary concurrency, recovery and transaction processing

Pros:

Cons:

DBAs may have to do extra work to ensure that the distributed mature of the system is transparent
Difficult to maintain integrity, which require too much of the network's resources to be feasible

Data is stored in many locations
Several owners of data and therefore no certainly of availability or consistency of data
No standards have been developed except in case of XML/http and some protocols for accessing data in WWW
Convenient to use
Notions of transactions is much more difficult to enforce

Data and Processing are shared among a group of computer systems which may be geographically separated
Computer nodes can join and leave the network at will, thus need duplication of data for availability and reliability
Reliability and security of such systems can be worse than grid database

Data and Processing are shared among a group of computer systems which may be geographically separated
The grid database system is designed for particular purpose
Administration of such systems are done locally by each owner of the system
Reliability and security of such system are not well-developed or studied.

Cluster, Grid and Cloud Computing

Cluster differs from Cloud and Grid in that a cluster is a group of computers connected by a local area network (LAN), whereas cloud and grid are more wide scale and can be geographically distributed. Another way to put it is to say that a cluster is tightly coupled, whereas a Grid or a cloud is loosely coupled.
Clusters are made up of machines with similar hardware, whereas clouds and grids are made up of machines with possibly very different hardware configurations.
Cloud services offered in several forms:
- IaaS Infrastructure as a service(provide virtual machines)
- PaaS Platform as a service(provide environment like Linux)
- SaaS Software as a service (Specific application like RDB)
  the datacenter hardware and software is what we call a cloud
Cloud computing is a centralized model whereas grid computing is a decentralized model where the computation could occur over many administrative domains.
A grid is a collection of computers which is owned by multiple parties in multiple locations and connected together so that users can share the combined power of resources. Whereas a cloud is a collection of computers usually owned by a single party.

Examples of Clouds: Amazon Web Services (AWS), Google App Engine.

Examples of Grids: FutureGrid.

Examples of cloud computing services: Dropbox, Gmail, Facebook, Youtube, RapidShare

Database Architecture