DISTRIBUTED DATABASE:

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  • A logically interrelated collection of shared data  and a description of this data physically distributed over a computer network which can be accessed by any node attached to that network.
  • In a distributed database storage devices are not all attached to a common processing unit such as the CPU ie, A distributed database system consists of loosely-coupled sites that share no physical components.
  • The software system that permits the management of the distributed database and makes the distribution transparent to users.
  • A Distributed Database Management System (DDBMS) consists of a single logical database that is split into a number of fragments.
  • Each fragment is stored on one or more computers under the control of a separate DBMS, with the computers connected by a communications network. Each site is capable of independently processing user requests that require access to local data (that is, each site has some degree of local autonomy) and is also capable of processing data stored on other computers in the network.
  • A distributed database can reside on network servers on the Internet, on corporate intranets or extranets, or on other company networks. 
  • Two processes ensure that the distributed databases remain up-to-date and current: replication and duplication.
    • Replication involves using specialized software that looks for changes in the distributive database. Once the changes have been identified, the replication process makes all the databases look the same. The replication process can be complex and time-consuming depending on the size and number of the distributed databases. This process can also require a lot of time and computer resources.
    • Duplication, on the other hand, has less complexity. It basically identifies one database as a master and then duplicates that database. The duplication process is normally done at a set time after hours. This is to ensure that each distributed location has the same data. In the duplication process, users may change only the master database. This ensures that local data will not be overwritten.
  • A database user accesses the distributed database through:
    • Local applications: Applications which do not require data from other sites.
    • Global applications: Applications which do require data from other sites.

2. Homogeneous database:

  • A homogeneous distributed database has identical software and hardware running all databases instances, and may appear through a single interface as if it were a single database.
  • All sites have identical software and are aware of each other and agree to cooperate in processing user requests. Each site surrenders part of its autonomy in terms of right to change schema or software.
  • The following conditions must be satisfied for homogeneous database:
    • The operating system used, at each location must be same or compatible.
    • The data structures used at each location must be same or compatible.
    • The database application (or DBMS) used at each location must be same or compatible.

2. Heterogeneous database:

  • A heterogeneous distributed database may have different hardware, operating systems, database management systems, and even data models for different databases.
  • Here different sites may use different schema and software. Difference in schema is a major problem for query processing and transaction processing.
  • Sites may not be aware of each other and may provide only limited facilities for cooperation in transaction processing. In heterogeneous systems, different nodes may have different hardware & software and data structures at various nodes.
  • Heterogeneous systems are usually used when individual sites use their own hardware and software. On heterogeneous system, translations are required to allow communication between different sites (or DBMS).
  • In this system, the users must be able to make requests in a database language at their local sites.
  • In this system, a user at one location may be able to read but not update the data at another location.
  • Care with a distributed database must be taken to ensure the following:

    • The distribution is transparent — users must be able to interact with the system as if it were one logical system. This applies to the system's performance, and methods of access among other things.
    • Transactions are transparent — each transaction must maintain database integrity across multiple databases. Transactions must also be divided into sub-transactions, each sub-transaction affecting one database system.

Advantages of Distributed Database

  • Management of distributed data with different levels of transparency like network transparency, fragmentation transparency, replication transparency, etc.
  • Increase reliability and availability
  • Easier expansion.
  • Reflects organizational structure — database fragments potentially stored within the departments they relate to
  • Local autonomy or site autonomy — a department can control the data about them (as they are the ones familiar with it)
  • Protection of valuable data — if there were ever a catastrophic event such as a fire, all of the data would not be in one place, but distributed in multiple locations
  • Improved performance — data is located near the site of greatest demand, and the database systems themselves are parallelized, allowing load on the databases to be balanced among servers. (A high load on one module of the database won't affect other modules of the database in a distributed database)
  • Economics — it may cost less to create a network of smaller computers with the power of a single large computer
  • Modularity — systems can be modified, added and removed from the distributed database without affecting other modules (systems)
  • Reliable transactions - due to replication of the database
  • Hardware, operating-system, network, fragmentation, DBMS, replication and location independence
  • Continuous operation, even if some nodes go offline (depending on design)
  • Distributed query processing can improve performance
  • Distributed transaction management
  • Single-site failure does not affect performance of system.
  • All transactions follow A.C.I.D. property:
    • A-atomicity, the transaction takes place as a whole or not at all
    • C-consistency, maps one consistent DB state to another
    • I-isolation, each transaction sees a consistent DB
    • D-durability, the results of a transaction must survive system failures

Disadvantages of Distributed Database

  • Complexity - DBAs may have to do extra work to ensure that the distributed nature of the system is transparent. Extra work must also be done to maintain multiple disparate systems, instead of one big one. Extra database design work must also be done to account for the disconnected nature of the database - for example, joins become prohibitively expensive when performed across multiple systems.
  • Economics — increased complexity and a more extensive infrastructure means extra labour costs
  • Security — remote database fragments must be secured, and they are not centralized so the remote sites must be secured as well. The infrastructure must also be secured (for example, by encrypting the network links between remote sites).
  • Difficult to maintain integrity — but in a distributed database, enforcing integrity over a network may require too much of the network's resources to be feasible
  • Inexperience — distributed databases are difficult to work with, and in such a young field there is not much readily available experience in "proper" practice
  • Lack of standards — there are no tools or methodologies yet to help users convert a centralized DBMS into a distributed DBMS
  • Database design more complex — In addition to traditional database design challenges, the design of a distributed database has to consider fragmentation of data, allocation of fragments to specific sites and data replication
  • Additional software is required
  • Operating system should support distributed environment
  • Concurrency control poses a major issue. It can be solved by locking and timestamping.
  • Distributed access to data
  • Analysis of distributed data

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