Distributed Database Concept
Introduction , Component of DDBMS and Differentiate b/n Distributed Database & Distributed Processing.
Introduction:
A distributed database is a database that is spread across multiple nodes or locations in a computer network. Unlike a centralized database, where all data is stored in a single location, a distributed database allows for data to be stored and accessed in a distributed manner. This enables improved scalability, availability, and performance of the database system.
Components of DDBMS (Distributed Database Management System):
1. Data Fragmentation and Replication: Data fragmentation involves dividing the database into smaller fragments, while data replication involves creating copies of the data at different nodes. These techniques help distribute the data across multiple nodes, enhancing data availability and performance.
2. Data Distribution Transparency: This component ensures that users and applications are unaware of the physical location of data. It provides a unified view of the database, regardless of where the data is physically stored.
3. Transaction Management: Distributed databases support distributed transactions, which involve multiple database operations across different nodes. Transaction management ensures the consistency and atomicity of distributed transactions, allowing them to be executed reliably and efficiently.
4. Concurrency Control: Distributed databases handle multiple transactions concurrently. Concurrency control mechanisms ensure that conflicts between concurrent transactions are resolved correctly and that data consistency is maintained.
5. Distributed Query Processing: Distributed query processing involves optimizing and executing queries that involve multiple data fragments located at different nodes. It aims to minimize the communication and processing costs involved in executing distributed queries.
Differentiate between Distributed Database and Distributed Processing:
Distributed Database:
- A distributed database refers to the physical distribution of data across multiple nodes in a network.
- Data is stored and managed in a distributed manner, allowing for improved scalability, availability, and performance.
- Database operations can be executed on different nodes concurrently, allowing for parallel processing and enhanced throughput.
- Consistency, data replication, and data distribution transparency are key factors in a distributed database.
Distributed Processing:
- Distributed processing refers to the execution of a single task or operation across multiple nodes in a network.
- It involves breaking down a task into multiple sub-tasks and distributing them across different nodes for parallel execution.
- Distributed processing can be applied to various computing tasks, not just database operations.
- The focus is on improving task execution time and efficiency by leveraging the computational power of multiple nodes.
- Data distribution and replication may or may not be involved in distributed processing, depending on the specific task.