Which mechanism helps ensure data integrity across distributed databases used in MIPC?

• A. Rely only on user discipline.
• B. Disable replication to reduce complexity.
• C. Use only eventual consistency.
• D. Constraints, checksums, transactions, replication consistency, versioning, and robust error handling.

Answer: (D)

Maintaining data integrity across distributed databases relies on a coordinated set of controls that validate, detect, coordinate, and recover from errors. Constraints enforce valid data states at write time—such as keys, referential integrity, and value restrictions—so invalid records never enter the system. Checksums help detect data corruption during transmission or storage, ensuring what’s stored or moved remains intact. Transactions provide atomicity and consistency for operations that span multiple records or nodes, so a multi-step update either fully succeeds or is rolled back. Replication consistency keeps data copies across nodes aligned, preventing reads from returning stale or divergent information. Versioning tracks changes and helps identify and resolve conflicting updates, while robust error handling ensures failures are detected, retried when sensible, and logged for auditing and recovery.

Relying on user discipline isn’t scalable or reliable for preserving integrity, and turning off replication removes redundancy and resilience. Using only eventual consistency can allow divergence between nodes, leading to inconsistent reads. The combination of constraints, checksums, transactions, replication consistency, versioning, and strong error handling provides a comprehensive approach to preserving data integrity across distributed databases used in MIPC.