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Documentation Index

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Full sync re-reads the selected table or resource on every run. It is the safest place to start when you are onboarding a new source, validating a transform, or syncing a small dataset that changes infrequently.

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When teams use full sync

  • small reference tables such as countries, tax_rates, or warehouse_locations
  • SaaS resources where a reliable cursor field is not available or not needed
  • first-run validation before moving a larger table to incremental sync
  • controlled nightly refreshes where simplicity matters more than read efficiency

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Step by step in MantrixFlow

  1. Create and test the source and destination connections.
  2. Go to Data Pipelines → + New Pipeline, name the pipeline, pick the source connection, and click Create & open canvas.
  3. Click ⚙️ on the Source node — click Discover schema, tick Include on the table, click Preview to verify rows.
  4. Add a Transform node if you need cleanup, renaming, or filtering.
  5. Click ⚙️ on the Destination node — open the Config tab:
    • Set Connection, Final delivery schema
    • Set Sync mode to FULL_TABLE
    • Set Write mode to Upsert
    • Click Validate config
  6. Open the Destination Preview tab to confirm the target table.
  7. Click ▷ to run manually and check the history icon for results.
  8. Once the run succeeds, open the Scheduling tab to add a schedule.

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Real-world example

Lighthouse Commerce keeps a small public.tax_rates table in PostgreSQL and syncs it into a PostgreSQL reporting database every night. Because the dataset is small and correctness matters more than optimization, full sync is the cleanest option.

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Why full sync is a good first production step

  • it removes cursor complexity while you validate field shape
  • it makes debugging easier because every run processes the same logical dataset
  • it is usually the fastest way to prove that the connection, transform, and destination naming are correct