Challenges with Strong Consistency
- Performance: Maintaining consistent data across multiple nodes requires additional communication and coordination, impacting performance.
- Complexity: Implementing and maintaining strong consistency protocols can be complex and require significant expertise.
- Scalability: As the number of nodes increases, the cost of maintaining consistency can become prohibitive.
- Availability: Strong consistency guarantees can be difficult to maintain in the presence of network failures or node outages.
- Increased Latency: Synchronization mechanisms required for strong consistency introduce latency in read and write operations, impacting overall system performance.
- Reduced Availability: Under network partitions or failures, ensuring strong consistency may result in reduced availability as nodes may need to wait for synchronization before serving read requests.
Strong Consistency in System Design
Consistency in a system refers to the similarity and consistency of data and behavior across all its components. This ensures that users encounter the same version of the data and experience the expected system performance, regardless of which part of the system they interact with. Maintaining this uniform and reliable experience is vital for user satisfaction. Consistency in system design plays an important role in ensuring reliability, predictability, and correctness in software and hardware systems.
Important Topics for the Strong Consistency in System Design
- Importance of Data Consistency in Systems
- What is Strong Consistency?
- Characteristics of Strong Consistency
- Strong Consistency Comparison with Other Consistency Models
- Types of Strong Consistency
- Ways to achieve Strong Consistency
- Challenges with Strong Consistency
- Example of Strong Consistency
- Impact of Strong Consistency on System Performance, Scalability and Availability
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