What Is Scheduled Synchronization?

Scheduled synchronization (also called batch sync) transfers data on a timetable — every five minutes, every hour, every night — rather than in response to individual events.

How it works

1. A scheduler starts the job.
2. The job reads its checkpoint: the point up to which the previous run succeeded.
3. It queries the source for records changed after the checkpoint (minus a small overlap window).
4. It processes or enqueues each record, writing to the target idempotently.
5. Only when everything succeeds does it advance the checkpoint.

Advantages

• Simplicity: one job, clear start and end, easy to rerun.
• Predictable load: you choose when it runs, including off-peak.
• Bulk efficiency: many APIs offer bulk or batch endpoints suited to scheduled jobs.
• No public endpoint required.
• Natural reconciliation: a full comparison run is just another scheduled job.

Disadvantages

• Staleness: data can be up to one interval old.
• Wasted runs: jobs run even when nothing changed.
• Burst load: a large backlog can produce heavy bursts.

Design rules

• Never advance the checkpoint before processing completes.
• Use overlap windows and idempotent writes.
• Prevent overlapping runs with a lock, or a slow run can collide with the next one.
• Monitor last success time, duration, and records processed; alert when a run has not succeeded for longer than expected.
• Request minimal data in change queries; fetch details only for changed records.

Where it fits

Scheduled sync is ideal for catalog updates, price lists, nightly inventory reconciliation, financial postings, and ERPs that import in batches. For time-sensitive data, combine it with event-driven updates — see real-time vs. scheduled synchronization.

Summary

Scheduled synchronization moves changed data at fixed intervals using checkpoints. It is simple, predictable, and efficient, at the cost of freshness. Implement it with careful checkpoints, overlap windows, idempotent writes, and run monitoring.