Datasynchronization

Datasynchronization, also known as data synchronization, is the process of ensuring that two or more data sources reflect the same information over time. It involves detecting changes, propagating updates, and reconciling divergent copies. Synchronization can be one-way, where a primary source pushes changes to replicas, or two-way, where updates may occur at multiple locations and must be reconciled to maintain consistency. It is used across databases, file systems, cloud services, and mobile or edge devices.

Techniques include log-based replication and change data capture (CDC), which record updates as events; streaming replication that pushes events in near real time; and batch synchronization that runs at scheduled intervals. Architectures include client-server with central repositories, multi-master or masterless systems, and peer-to-peer networks. Consistency models range from strong consistency to eventual or causal consistency; the choice affects latency, availability, and conflict likelihood. Conflict resolution strategies include last writer wins, merge with application-defined rules, and automatic reconciliation using operational transformation or CRDTs.

Key considerations are data identity and versioning, idempotent operations, ordering guarantees, and schema evolution. Data protection and privacy must be maintained during transfer, with encryption in transit and at rest, access controls, and auditing.

Applications include database replication, online file synchronization services, mobile offline editing, IoT data collection, and collaborative editing. Challenges include network partitions, clock skew, data conflicts, and scaling to large datasets or high update rates.