A Distributed Database is a collection of data that is spread across multiple physical locations, interconnected via a network. Each site, or node, operates independently, processing local transactions while contributing to the overall database system. This architecture enhances the database’s availability and resilience to failures.
Distributed database is different from centralized database in the following ways:
| Aspect | Centralized Database | Distributed Database |
|---|---|---|
| Definition | A single database stored in one place. | A database spread across different locations, connected through a network. |
| Data Storage | All data is kept in one central location. | Data is divided and stored in multiple locations or servers. |
| Access Time | Can be slow if many users access it at the same time. | Usually faster, as users can access data from the nearest server. |
| Data Management | Easier to handle since everything is in one place. | Harder to manage due to multiple locations and synchronization. |
| Data View | Provides a complete and clear view to users. | Can be difficult to maintain a uniform view due to data being spread out. |
| Data Consistency | High consistency since all data is in one place. | May have consistency issues if the same data is stored in multiple locations. |
| System Failure | If the central database fails, everything stops working. | If one part fails, the rest can still work, improving reliability. |
| Cost | Cheaper as it has a simple setup. | More expensive due to complex infrastructure and management. |
| Maintenance | Easier to maintain as everything is in one place. | Harder to maintain as data is spread across different locations. |
| Efficiency | May become slow when handling large amounts of data. | More efficient for users in different locations as they access nearby data. |
| Response Speed | Can slow down when many users access it. | Usually faster, especially for local users. |
| Advantages | – Easy to control and secure. – Simple access control. – Easy to move data. | – Faster and better performance. – More reliable and always available. – Each location can operate independently. |
| Disadvantages | – Can slow down with too many users. – If it fails, everything stops. – Hard to expand. | – More complicated and expensive. – Harder to keep data consistent. – Requires advanced technology. |
| Examples | – Mainframe computers. – Large business databases. | – Apache Cassandra. – Amazon SimpleDB. – Apache HBase. |