Database Architecture
2018-06-13 本文已影响0人
KevinWu12
Centralized database system (CDB)
- 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
Distributed database system (DBAs):
- 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:
- Increase the reliability and availability
- Increase the scalability
- Protection of valuable data
- Distributed query processing cam improved performance
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
World Wide Web
- 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
P2P Database
- 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
Grid Computing
- 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