Data Synchronization
The process of managing and provisioning computer data centers through machine-readable definition files, rather than physical hardware configuration or interactive configuration tools.
Modes: 1. One-way (Mirroring). 2. Two-way (Bidirectional). 3. Continuous (Real-time). Techniques: File-level vs Block-level sync, delta encoding, version vectors, last-writer-wins resolution.
graph LR
Center["Data Synchronization"]:::main
Rel_synthetic_biology["synthetic-biology"]:::related -.-> Center
click Rel_synthetic_biology "/terms/synthetic-biology"
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🧒 Explain Like I'm 5
Imagine you and your friend are both writing in the same diary at the same time in different houses. Synchronization is like having a magic pen that copies everything you write into your friend's diary, and everything they write into yours, instantly. If you both try to write on the same line at once, the magic pen decides whose writing should stay. It keeps both diaries identical.
🤓 Expert Deep Dive
Technically, synchronization is governed by the 'CAP Theorem' (Consistency, Availability, Partition Tolerance). In a distributed system, you must trade off between 'Strong Consistency' (all nodes see the same data at the same time) and 'High Availability' (the system stays up even if some parts fail). 'Eventual Consistency' is a common model where the system guarantees that if no new updates are made, all nodes will eventually converge to the same state. Implementation methods include 'Change Data Capture' (CDC), which monitors database logs for changes, and 'Consensus [Algorithms](/en/terms/consensus-algorithms)' like Raft or Paxos, which allow a cluster of servers to agree on a single 'Truth' in the presence of failures.