Prompt
Airbyte schema drift
Latest observation
Airbyte schema drift usually means the source schema changed, but the destination schema in your sync didn’t fully update to match.
Common symptoms
- New columns appear in the source but not in the destination
- Syncs fail after a source table changes
- Data types no longer match
- Records are dropped, truncated, or nested fields change unexpectedly
Common causes
- A column was added/removed/renamed in the source
- A nested JSON field changed shape
- The connector’s schema discovery is stale
- Destination doesn’t support automatic schema evolution for that change
- Incremental sync with historical records and altered schema
What to do
- Run a schema refresh / discover in Airbyte
- Check the source connector logs for schema change or parsing errors
- Review destination settings:
- Does it auto-add columns?
- Does it require manual schema changes?
- Resync the stream if needed
- If using dbt or downstream models, update transformations to handle new/removed fields
If you want to prevent it
- Use stable schemas where possible
- Version your source API/DB schema changes
- Monitor schema changes in Airbyte sync logs
- Use normalization / transformations carefully for semi-structured data
If you want, I can also help with:
- Airbyte schema drift troubleshooting
- How Airbyte handles schema evolution for a specific source/destination
- A practical checklist for fixing a broken sync
Observation history
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