Parallel and Distributed Computing

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Distributed Databases

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Parallel and Distributed Computing

Definition

A distributed database is a database that is not stored in a single location but is distributed across multiple physical locations. These databases allow data to be stored on different servers, enabling improved access, fault tolerance, and scalability. The data can be spread across various sites that can be connected via a network, and they can function as if they are part of a single system, providing significant advantages in terms of performance and reliability.

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5 Must Know Facts For Your Next Test

  1. Distributed databases enhance fault tolerance by allowing operations to continue even if one or more nodes fail.
  2. Data can be distributed based on various strategies, including horizontal partitioning, vertical partitioning, or replication.
  3. They can improve performance by allowing parallel processing of queries across multiple nodes, reducing response time.
  4. Distributed databases often use specialized protocols for communication between nodes to ensure data integrity and consistency.
  5. They are widely used in cloud computing environments to facilitate large-scale applications and services with dynamic workloads.

Review Questions

  • How do distributed databases improve fault tolerance and data availability?
    • Distributed databases enhance fault tolerance by spreading data across multiple servers. If one server fails, the system can still operate using replicas from other locations, ensuring that data remains accessible. This redundancy allows for continued service and minimizes downtime, making distributed databases particularly reliable for critical applications.
  • Discuss the strategies used for distributing data in a distributed database and their impact on performance.
    • Data in a distributed database can be divided using horizontal partitioning, vertical partitioning, or replication. Horizontal partitioning involves splitting tables into rows across different servers, while vertical partitioning divides them into columns. Replication involves creating copies of the entire database or specific parts. These strategies significantly impact performance by allowing concurrent access to data and enabling parallel processing of queries, leading to faster response times and improved overall efficiency.
  • Evaluate the challenges associated with maintaining consistency in distributed databases and their implications for application development.
    • Maintaining consistency in distributed databases poses challenges due to the potential for network delays and partitioning issues. Developers must choose appropriate consistency models to ensure that all nodes reflect the same state of data, which can complicate application logic. This choice impacts performance; strong consistency may slow down operations due to synchronization requirements, while eventual consistency could lead to temporary discrepancies. Balancing these trade-offs is crucial for building reliable and efficient applications.
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