Database develop. life cycle - Centralized vs. distributed databases

1. Centralized Database

Definition:

• All data is stored and managed in a single location (server or mainframe).

• Users access the data through terminals or client applications connected to the central server.

Characteristics:

• Single point of control and management.

• Easier to maintain and backup.

• All users share the same database instance.

Advantages:

• Simpler design and administration.

• Data consistency is easier to maintain.

• Strong security control since everything is in one place.

Disadvantages:

• Limited scalability; server can become a bottleneck.

• Single point of failure → if the server crashes, the whole system is down.

• Slower access for geographically distant users.

Example:

• Traditional payroll systems or a university database hosted on a single server.

2. Distributed Database

Definition:

• Data is stored across multiple locations (servers) connected via a network.

• Each location can process queries locally or coordinate with others.

Characteristics:

• Data can be replicated or fragmented across sites.

• Supports multiple locations for better performance and reliability.

• Users may not know the physical location of data (transparent access).

Advantages:

• Better scalability: add more nodes to handle growth.

• High availability and fault tolerance: if one node fails, others can continue.

• Can improve performance for geographically distributed users.

Disadvantages:

• More complex design and administration.

• Maintaining consistency across sites is challenging.

• Higher cost for setup, network, and management.

Example:

• Google Spanner, Amazon DynamoDB, or a global banking system where branches share data.

Quick Comparison Table

Summary:

• Centralized → simple, consistent, but limited scalability and reliability.

• Distributed → scalable, reliable, better performance across locations, but complex and costly.