Distributed database systems

Definition

Distributed database systems are databases that are not stored in a single location but are spread across multiple sites, often connected through a network. This setup allows for data to be stored in different geographical locations while providing users with a unified view of the data. Such systems enhance availability, scalability, and fault tolerance, making them suitable for a variety of applications and use cases.

5 Must Know Facts For Your Next Test

1. Distributed database systems can be classified into two main types: homogeneous, where all nodes use the same DBMS, and heterogeneous, where different DBMSs are used at different sites.
2. One major advantage of distributed databases is improved performance since data can be accessed from multiple locations simultaneously, reducing latency.
3. These systems often employ various strategies for data distribution and replication, which help in enhancing fault tolerance and ensuring continuous availability even if some nodes fail.
4. The CAP theorem states that in a distributed database system, you can only guarantee two out of the following three: Consistency, Availability, and Partition Tolerance.
5. Distributed databases are particularly useful in cloud computing environments, where resources can be dynamically allocated and scaled based on demand.

Review Questions

• How do distributed database systems improve performance compared to traditional centralized databases?
  • Distributed database systems improve performance by allowing data to be accessed from multiple locations at the same time, which reduces latency and increases throughput. This means users can query and retrieve information more quickly since the system can balance the load across various nodes. Furthermore, by distributing the data geographically closer to users, it minimizes delays caused by network traffic.
• Discuss the importance of replication in distributed database systems and its impact on data availability.
  • Replication is crucial in distributed database systems as it ensures that copies of data exist at multiple locations. This redundancy enhances data availability because if one node goes down or becomes unreachable, users can still access the replicated data from another location. It also aids in load balancing, as read requests can be served from any replica, thereby improving performance while maintaining data consistency through synchronization protocols.
• Evaluate the challenges faced by distributed database systems concerning consistency models and how these challenges might influence system design.
  • Distributed database systems face significant challenges related to consistency models due to the nature of data being spread across various nodes. Different nodes may receive updates at different times, leading to potential discrepancies in data. System designers must choose between strong consistency, which ensures immediate visibility of updates at all nodes but may reduce availability, or eventual consistency, which allows for temporary inconsistencies but improves availability. These choices significantly affect how applications are built and how they handle user interactions with the database.

Related terms

Replication: The process of copying and maintaining database objects, such as tables or rows, in multiple locations to improve data availability and reliability.

Data Fragmentation: The technique of dividing a database into smaller, manageable pieces or fragments that can be distributed across multiple sites, enhancing performance and access speed.

Consistency Models: Protocols that define the rules for how data is synchronized and made consistent across distributed systems, addressing challenges related to concurrent updates and data integrity.