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Types of Distributed DBMS

Last Updated : 07 Sep, 2023
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A system that is used for managing the storage and retrieval of data across multiple interconnected databases is called a Distributed Database Management System(DDBMS). In this case, the interconnected databases are situated in different geographical areas. In DDBMS, one can access and store data transparently from different geographical locations and ensure high availability, scalability, and fault tolerance mechanisms. DDBMSs are designed to handle huge amounts of data spread across different sites. It can give seamless performance in data sharing and collaboration by organizations.

Features of Distributed DBMS

There is a presence of a certain number of features that make DDBMS very popular in organizing data.

  • Data Fragmentation: The overall database system is divided into smaller subsets which are fragmentations. This fragmentation can be three types horizontal (divided by rows depending upon conditions), vertical (divided by columns depending upon conditions), and hybrid (horizontal + vertical).
  • Data Replication: DDBMS maintains and stores multiple copies of the same data in its different fragments to ensure data availability, fault tolerance, and seamless performance.
  • Data Allocation: It determines if all data fragments are required to be stored in all sites or not. This feature is used to reduce network traffic and optimize the performance.
  • Data Transparency: DDBMS hides all the complexities from its users and provides transparent access to data and applications to users.

Types of Distributed DBMS

There are 6 types of DDBMS present there which are discussed below:

  • Homogeneous: In this type of DDBMS, all the participating sites should have the exact same DBMS software and architecture which makes all underlying systems consistent across all sites. It provides simplified data sharing and integration.
  • Heterogeneous: In this type of DDBMS, the participating sites can be from multiple sites and use different DBMS software, data models, or architectures. This model faces little integration problem as all site’s data representation and query language can be different from each other.
  • Federated: Here, the local databases are maintained by individual sites or federations. These local databases are connected via a middleware system that allows users to access and query data from multiple distributed databases. The federation combines different local databases but maintains autonomy at the local level.
  • Replicated: In this type, the DDBMS maintains multiple copies of the same data fragment across different sites. It is used to ensure data availability, fault tolerance, and seamless performance. Users can access any data from the nearest replica if the root is down for some reason. However, it is required to perform high-end synchronization of data changes in replication.
  • Partitioned: In a Partitioned DDBMS, the overall database is divided into distinct partitions, and each partition is assigned to a specific site. Partitioning can be done depending on specific conditions like date range, geographic location, and functional modules. Each site controls its own partition and the data from other partitions should be accessed through communication and coordination between sites.
  • Hybrid: It is just a combination of multiple other five types of DDBMS which are discussed above. The combination is done to address specific requirements and challenges of complex distributed environments. Hybrid DDBMS provides more optimized performance and high scalability.


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