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Database Architecture

Database Architecture

作者: KevinWu12 | 来源:发表于2018-06-13 19:47 被阅读0次
    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

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