Introduction of DDBMS

  • Distributed databases (DDBMS) play a crucial role in modern computing, having higher scalability, availability, and performance in handling large volumes of data across geographically dispersed locations.


  • Distributed databases store data across multiple physical or logical locations, providing improved scalability, fault tolerance, and performance by distributing data processing and storage tasks across a network of interconnected nodes.


  • Data Distribution: In DDBMS, Data is partitioned according to need and stored across multiple nodes or servers in a network.
  • Replication: In this, several copies of data may exist on multiple nodes/locations to ensure fault tolerance and availability.
  • Autonomy: It supports Autonomy i.e., each node in a distributed database system that may operate independently, contributing to its portion of the data separately.
  • Concurrency Control: Distributed databases implement mechanisms or tools to manage concurrent access and ensure data consistency across multiple nodes, especially during concurrent updates.
  • Transactions and ACID Properties: It maintains transactional integrity and consistency through mechanisms supporting the basic rules of DBMS, i.e., Atomicity, Consistency, Isolation, and Durability (ACID).

Types of DDBMS

  • There are two types of DDBMS –
    • Homogeneous Distributed Database: In this, there are similar DBMSs that exist across all nodes in the distributed system.
    • Heterogeneous Distributed Database: In this, there are different types or versions of DBMS that exist across all the different nodes, requiring additional translation or middleware for communication.

Advantages of DDBMS

  • It has the following advantages –
    • Scalability: It enables horizontal scaling by adding more new required nodes in the systems to accommodate increased data or load.
    • Fault Tolerance: It uses redundant copies of data to ensure system availability even if some nodes fail/crash suddenly.
    • Performance: It supports distributed processing and hence reduces network traffic and latency for local access to data.
    • Geographical Distribution: It supports global access and reduces the data access time by placing data closer to the end-user’s locations or nodes.
    • Data Consistency: It ensures data consistency across distributed nodes, especially during concurrent updates.
    • Network Complexity: It manages complex network communication, synchronization, and data transfer across a distributed environment.
    • Security and Privacy: It ensures data security, access control, and compliance across heavily distributed nodes.
    • Blockchain Technology: Distributed DBMS technology supports the new modern concept of decentralization, transparency, and immutability for transactional data which is used at large scale in Blockchain technology.
    • Edge Computing: The concept of distributed databases is used in optimizing edge devices to support IoT and real-time data processing at the network edge.

Disadvantages of DDBMS

  • DDBMS setup cost is high.
  • DDBMS supports data duplicacy.
  • Designing and maintaining a distributed database is complex and requires expertise and careful planning.

Examples of DDBMS

Bigtable (Google Cloud), Amazon DynamoDB(NoSQL databases), Cassandra(NoSQL databases), etc.


Categories: DBMS


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