Distributed Databases in DBMS-Download Free Handwritten Notes :
## 📖 Introduction
Database systems play a critical role in managing, storing, and retrieving data efficiently. Among the various architectures in database management systems (DBMS), **Distributed Database Systems** and **Client-Server Architecture** stand out for their scalability and efficiency. Both architectures are designed to handle large volumes of data and support modern applications by leveraging networked systems.
What is a Distributed Database?
A **Distributed Database System** is a type of database where data is stored across multiple physical locations. These locations can be on different machines or geographical regions, yet the system functions as a single database
Features of Distributed Databases
- **Data Distribution**: Data is divided across various locations for efficiency and fault tolerance.
- **Transparency**: Users interact with the database as if it were centralized, despite being distributed.
- **Redundancy Management**: Copies of the same data are maintained to ensure reliability.
- **Scalability**: Easily expands with the addition of new nodes.
Advantages
– Improved reliability through data replication.
– Enhanced performance by localizing queries.
– Better fault tolerance and availability.
Challenges
– High complexity in synchronization and consistency management.
– Increased cost of maintaining multiple locations.
What is Client-Server Architecture?
In **Client-Server Architecture**, a database system consists of clients and a central server. Clients request services, while the server processes and responds to these requests
### Features of Client-Server Architecture
- **Centralized Control**: The server manages all database operations.
- **Multiple Clients**: Many clients can connect simultaneously to the server.
- **Resource Sharing**: Efficient sharing of computational and database resources.
### Advantages
– Centralized data management ensures data integrity.
– Easy to maintain and manage from a single server.
– Supports scalability through additional clients.
### Challenges
– Server overload with multiple simultaneous requests.
– Performance depends heavily on the network.
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