Data Sync

* Scheduling Guide

Data sync schedules drive ETL pipelines, feed ingestion, and cross-system replication. The right frequency depends on the acceptable lag in your downstream consumers: analytical dashboards can tolerate hourly or daily sync while operational systems may need near-real-time data. A common pattern is to run a full sync nightly (catching any missed delta records) and an incremental sync every few minutes during business hours. Scheduling data sync jobs requires awareness of upstream availability windows — syncing from a database that runs its own maintenance at 3 AM will produce empty or partial results unless you offset your schedule by 30–60 minutes. Always build idempotency into the job so re-running a failed sync does not duplicate records.