A Distributed Database Management System (DDBMS) is a software system that manages a database distributed across multiple locations, interconnected by a network, yet presents it as a unified database to users. This distribution allows data to be stored closer to where it’s needed, enhancing accessibility and performance.
The key characteristics of a DDBMS are:
i. Data Distribution: Data is divided into fragments, which may be replicated and allocated across various sites.
ii. Autonomy: Each site operates independently, managing its own data while participating in global applications.
iii. Network Connectivity: Sites are linked via a communications network, enabling data sharing and coordination.
Distributed Database Management Systems (DDBMS) can be organized using various architectures, each with distinct structures and functionalities. The three primary architectures are:
1. Client-Server Architecture: In this setup, multiple clients (user interfaces) connect to one or more servers (data storage and management systems) over a network. Clients send queries to the servers, which process these requests and return the results, centralizing data management and simplifying maintenance and control.
The advantages of client-server architecture are as follows:
i. Implementation is simplified due to centralized servers.
ii. Allows efficient resource utilization.
iii. Easier to manage and maintain as all data is stored in a central location.
iv. Provides better security and access control.
The disadvantages of client-server network are as follows:
i. Server overload can occur with numerous client requests, leading to performance bottlenecks.
ii. A single point of failure can disrupt the entire system.
iii. Scalability is limited compared to decentralized architectures.
iv. Network dependency may cause delays if connectivity issues arise.
2. Collaborating Server (Peer-to-Peer) Architecture: In this structure, multiple servers, each with its own database, collaborate without a centralized authority. These servers coordinate to process queries by dividing tasks among themselves and aggregating results for the client. This architecture enhances system reliability and scalability, as each server can function independently and share workloads.
The advantages of a collaborating server (peer to peer) architecture are as follows:
i. Enhances system reliability as there is no single point of failure.
ii. Improves scalability since each server can function independently.
iii. Distributes workload efficiently, reducing server overload.
iv. Provides better fault tolerance and availability.
The disadvantages of a collaborating server (peer to peer) architecture are as follows:
i. Complex coordination mechanisms are required to maintain data consistency.
ii. Query processing can be challenging due to data distribution.
iii. Higher communication overhead among servers.
iv. Increased complexity in managing and synchronizing multiple databases.
3. Middleware (Multidatabase) Architecture:
In this architecture, an additional software layer called middleware sits between clients and multiple heterogeneous databases. The middleware manages communication, query processing, and transaction management across different databases, providing a unified interface to the clients. This approach enables the integration of diverse databases without modifying their underlying structures, facilitating interoperability. However, it also introduces additional complexity and potential performance overhead due to the extra middleware layer.
The advantages of middleware architecture are as follows:
i. Enables integration of diverse databases without modifying their underlying structures.
ii. Facilitates interoperability between different database systems.
iii. Provides a unified interface for clients, simplifying access to distributed data.
iv. Enhances flexibility by allowing different database management systems to work together.
The disadvantages of middleware architecture are as follows:
i. Introduces additional complexity in system design and management.
ii. Increases performance overhead due to the extra middleware layer.
iii. Requires efficient query optimization and transaction management mechanisms.
iv. Potential delays in data processing due to middleware handling requests.
Thus, each DDBMS architecture has its own strengths and challenges, making the choice dependent on system requirements and scalability needs. Proper selection and implementation ensure efficient data management, accessibility, and performance.