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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