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Handle client-server sync challenges #2

@rahuldahal

Description

@rahuldahal

Problem

  1. Latency: Network delays can affect the responsiveness of interactions between the client and server. High latency can lead to slow updates and a less responsive user experience.

  2. Consistency: Ensuring that the client and server have a consistent view of data can be tricky, especially in systems with frequent updates. Techniques like eventual consistency, strong consistency, and conflict resolution are often used.

  3. Concurrency: Managing simultaneous updates from multiple clients can lead to conflicts and data integrity issues. Implementing proper locking mechanisms or conflict resolution strategies is essential.

  4. Offline Handling: Clients may go offline temporarily, and the system needs a strategy to handle data changes that occur while offline, and synchronize them once connectivity is restored.

  5. Error Handling: Network failures, server crashes, or data corruption can disrupt synchronization. Robust error handling and retry mechanisms are needed to handle such scenarios gracefully.

  6. Scalability: As the number of clients grows, the server must handle increased load and manage synchronization efficiently. Load balancing, sharding, and other scaling strategies are important.

  7. Security: Data exchanged between client and server needs to be protected from unauthorized access or tampering. Implementing encryption, authentication, and authorization is crucial.

  8. Data Integrity: Ensuring that data remains accurate and consistent during synchronization processes. Techniques like checksums, versioning, and transactional updates help maintain integrity.

  9. State Management: Keeping track of the state on both the client and server side, especially when dealing with complex data structures or frequent updates, requires careful design.

  10. Performance: Efficiently synchronizing data without causing performance bottlenecks on the client or server. Techniques like delta updates (only sending changed data) can help improve performance.

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This real-time DB might be useful

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