What distinguishes distributed from centralized database systems?

2 Distributed Database Systems

A distributed database system is a system where the data is stored and accessed from multiple locations, such as different servers, computers, or devices. This means that there are multiple copies of the data, which can be synchronized or replicated across the network. A distributed database system also has a distributed control over the data access, security, and administration. Additionally, this type of system can be more resilient, have high scalability, low operational costs, and high performance. Specifically, it can tolerate failures without affecting the whole system, handle increasing data volumes and user demands by adding or removing nodes or resources, use cheaper and more available equipment and maintenance, and reduce network traffic, latency, and bottlenecks by distributing the workload and processing.

3 Types of Distributed Database Systems

Distributed database systems can be further classified into different types based on how the data is distributed and how the nodes communicate. Homogeneous systems are those where all the nodes use the same database management system (DBMS) and have the same schema and data structure, which simplifies data integration and query processing. Heterogeneous systems, however, involve nodes using different DBMSs and having different schemas and data structures, making data integration and query processing more complex and slower. Replicated distributed databases copy or duplicate data across all or some of the nodes, increasing availability and reliability but introducing the challenge of data consistency. Finally, fragmented distributed databases divide or partition the data into smaller pieces and distribute it across the nodes, improving locality and efficiency but introducing issues with data completeness and coordination.

4 Challenges of Distributed Database Systems

Distributed database systems offer many advantages over centralized database systems, however, they also come with a variety of challenges and trade-offs. Data consistency, synchronization, concurrency, and security are some of the major issues. Ensuring all copies or fragments of the data are identical across nodes can be affected by network delays, failures, or conflicts. Updating or transferring the data in a timely and accurate manner can be impacted by network bandwidth, availability, or security. Additionally, managing simultaneous access or modification of the data by multiple users or applications can be affected by locking, isolation, or transaction management. Lastly, protecting the data from unauthorized or malicious access or manipulation requires encryption, authentication, or authorization.

5 Solutions for Distributed Database Systems

Distributed database systems are complex and dynamic systems that require careful design and implementation. To optimize their performance, there are several solutions and techniques that can be employed. Data replication strategies, for example, determine how, when, and where the data is replicated across the nodes. These could be snapshot, lazy, eager, or hybrid replication. Additionally, data fragmentation strategies determine how, why, and where the data is fragmented across the nodes. Some of these strategies are horizontal, vertical, or hybrid fragmentation. Data allocation strategies decide how the data is assigned or distributed across the nodes. Common allocation strategies include centralized, decentralized, or hierarchical allocation. Lastly, data query processing strategies decide how the data is accessed or manipulated across the nodes. Common query processing strategies are centralized, distributed, or parallel query processing.