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Distributed Database Management System

Distributed Database Management System. DDBMS. In a distributed database, there are a number of databases that may be geographically distributed all over the world. A distributed DBMS manages the distributed database in a manner so that it appears as one single database to users.

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Distributed Database Management System

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  1. Distributed Database Management System

  2. DDBMS • In a distributed database, there are a number of databases that may be geographically distributed all over the world. A distributed DBMS manages the distributed database in a manner so that it appears as one single database to users. • A distributed database is a collection of multiple interconnected databases, which are spread physically across various locations that communicate via a computer network.

  3. Features of DDBMS • A distributed DBMS is a collection of logically related shared data. • The data in a distributed DBMS is split into a number of fragments or partitions. • Fragments may be replicated in a distributed system. • Fragments/replicas are allocated to different sites.

  4. In a distributed system, the sites are linked by communications network. • The data at each site is under the control of a DBMS. • The DBMS at each site has its own right, that is, it can handle local applications independently. • Each DBMS in a distributed system participates in at least one global application.

  5. DBMS functions to be classified & distributed. • Application Interface : used to interact with the end user application programs & other DBMS with in the DBMS. • Validation : To analyze data requests for syntax correctness. • Transformation : To decompose complex requests in to small data request components. • Query optimization : to find best access strategy.

  6. Mapping : To determine the data location of local & remote fragments. • I/O Interface : To read (or) write data from (or) to permanent local storage. • Security : Provide data privacy at both local & remote data base. • Backup & recovery : To ensure the availability & recoverability of the data base in case of a failure. • Concurrency control : Manage simultaneous data access & to ensure data consistency.

  7. DDBMS components : 1. Computer Work Stations:  DDBMS must be independent of the computer system hardware. 2.Network Hard-ware & Soft-ware Components : This is present in each work station . The network components allows all sites to internet & exchange data. Because the components like computers, as network hard ware & so on to be supplied by different vendors so that’s why DDBMS functions can be run on multiple platforms.

  8. 3. Communication Media : This carry the data from one workstation to another. The DDBMS must be communications media independent. It able to support several types of communication media. 4. Transaction Processor (TP): It is a software component found in each computer that requests data. TP receive & process the applications data requests. TP also known as application processor (AP) or the Transaction manager(TM). 5. Data processor  (DP) : It is a software component found in each computer that stores & retrieves data located at the size.

  9. Factors Encouraging DDBMS • Distributed Nature of Organizational Units • Need for Sharing of Data • Support for Both OLTP and OLAP • Database Recovery • Support for Multiple Application Software

  10. Advantages of DDBMSs: • Reflects organizational structure: We can distribute the data base over any organization offices which has distributed locations • Improved shareability and local autonomy: Users can use the data of other sites, which mean the data can be near of the users who use it. Also by this way the data can be controlled by the user. • Improved availability: Unlike centralized DBMS, the failure at one site or link of communication makes only some parts of system inaccessible, which means the entire system is still working.

  11. Improved performance: We can improve the accessing speed to data base if we use remote centralized database. Also, there may not be same conflict for CPU and using the services, like DBMS. • Economics: For making the organization systems more cost-effective to obtain separate computers, DBMS allows us to create systems of smaller computer, its power equal the power of one large computer. • Modular growth: This one refers to the flexibility of DDBMS, where we can add a new site without any affects on the operation of other sites.

  12. Improved reliability: The replication system make the data exist in many site. So this insures the possibility of accessing to this data if there is any failure happened.

  13. Disadvantages of DDBMSs: • Complexity: The features of DDBMS like replication, availability flexibility make the implementation of DDBMS more complex than centralized DBMS. • Cost: The cost will increase due to the complexity in DDBMS than centralized DBMS. It requires the maintenance and additional hardware to create a network between the posts. • Security: Unlike centralized system, access to data not only has to be secured, but the entire network also has to be made secure.

  14. Integrity control more difficult: In a DDBMS, the costs of processing and communication that we have to make to implement integrity constraints may be prohibitive. • Lack of standards: Despite there is effective communication when we use DDBMS, There are no methodologies or tools to assist users convert a centralized DBMS into a distributed DBMS. • Lack of experience: Unlike what we have with centralized DBMSs, still our experiences are lack in industry of DDBMS.

  15. Types of Distributed Databases • Distributed databases can be broadly classified into homogeneous and heterogeneous distributed database environments

  16. Types of Distributed Databases

  17. Homogeneous Distributed Databases In a homogeneous distributed database, all the sites use identical DBMS and operating systems. Its properties are − • The sites use very similar software. • The sites use identical DBMS or DBMS from the same vendor. • Each site is aware of all other sites and cooperates with other sites to process user requests. • The database is accessed through a single interface as if it is a single database.

  18. Types of Homogeneous Distributed Database There are two types of homogeneous distributed database − • Autonomous − Each database is independent that functions on its own. They are integrated by a controlling application and use message passing to share data updates. • Non-autonomous − Data is distributed across the homogeneous nodes and a central or master DBMS co-ordinates data updates across the sites.

  19. Heterogeneous Distributed Databases In a heterogeneous distributed database, different sites have different operating systems, DBMS products and data models. Its properties are − • Different sites use dissimilar schemas and software. • The system may be composed of a variety of DBMSs like relational, network, hierarchical or object oriented. • Query processing is complex due to dissimilar schemas.

  20. Transaction processing is complex due to dissimilar software. • A site may not be aware of other sites and so there is limited co-operation in processing user requests.

  21. Types of Heterogeneous Distributed Databases • Federated − The heterogeneous database systems are independent in nature and integrated together so that they function as a single database system. • Un-federated − The database systems employ a central coordinating module through which the databases are accessed.

  22. Distributed DBMS Architectures DDBMS architectures are generally developed depending on three parameters − • Distribution − It states the physical distribution of data across the different sites. • Autonomy − It indicates the distribution of control of the database system and the degree to which each constituent DBMS can operate independently. • Heterogeneity − It refers to the uniformity or dissimilarity of the data models, system components and databases.

  23. Architectural Models Some of the common architectural models are • Client - Server Architecture for DDBMS • Peer - to - Peer Architecture for DDBMS • Multi - DBMS Architecture

  24. Client - Server Architecture for DDBMS • This is a two-level architecture where the functionality is divided into servers and clients. The server functions primarily encompass data management, query processing, optimization and transaction management. Client functions include mainly user interface.

  25. Peer- to-Peer Architecture for DDBMS In these systems, each peer acts both as a client and a server for imparting database services. The peers share their resource with other peers and co-ordinate their activities. This architecture generally has four levels of schemas − • Global Conceptual Schema − Depicts the global logical view of data. • Local Conceptual Schema − Depicts logical data organization at each site. • Local Internal Schema − Depicts physical data organization at each site. • External Schema − Depicts user view of data.

  26. Multi - DBMS Architectures This is an integrated database system formed by a collection of two or more autonomous database systems. Multi-DBMS can be expressed through six levels of schemas − • Multi-database View Level − Depicts multiple user views comprising of subsets of the integrated distributed database. • Multi-database Conceptual Level − Depicts integrated multi-database that comprises of global logical multi-database structure definitions.

  27. Multi-database Internal Level − Depicts the data distribution across different sites and multi-database to local data mapping. • Local database View Level − Depicts public view of local data. • Local database Conceptual Level − Depicts local data organization at each site. • Local database Internal Level − Depicts physical data organization at each site.

  28. Design Alternatives The distribution design alternatives for the tables in a DDBMS are as follows − • Non-replicated and non-fragmented • Fully replicated • Partially replicated • Fragmented • Mixed

  29. Data Replication • Data replication is the process of storing separate copies of the database at two or more sites. It is a popular fault tolerance technique of distributed databases.

  30. Advantages of Data Replication • Reliability  • Reduction in Network Load  • Quicker Response  • Simpler Transactions 

  31. Disadvantages of Data Replication • Increased Storage Requirements  • Increased Cost and Complexity of Data Updating  • Undesirable Application – Database coupling 

  32. Fragmentation • Fragmentation is the task of dividing a table into a set of smaller tables. The subsets of the table are called fragments. Fragmentation can be of three types: horizontal, vertical, and hybrid (combination of horizontal and vertical). Horizontal fragmentation can further be classified into two techniques: primary horizontal fragmentation and derived horizontal fragmentation.

  33. Advantages of Fragmentation • Since data is stored close to the site of usage, efficiency of the database system is increased. • Local query optimization techniques are sufficient for most queries since data is locally available. • Since irrelevant data is not available at the sites, security and privacy of the database system can be maintained.

  34. Disadvantages of Fragmentation • When data from different fragments are required, the access speeds may be very high. • In case of recursive fragmentations, the job of reconstruction will need expensive techniques. • Lack of back-up copies of data in different sites may render the database ineffective in case of failure of a site.

  35. The three dimensions of distribution transparency are − • Location transparency • Fragmentation transparency • Replication transparency

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