DATA OPS
Cross-Warehouse Replication Schema-Drift Reconciler
Compares the schema of source tables in Postgres against their replicated copies in Snowflake, flags any columns that exist on one side but not the other or whose types diverged.
How it runs
The automated pipeline, trigger to output.
- TriggerDaily schedule starts reconciler
- ActionRead source column definitions from PostgresPostgres
- ActionRead replica column definitions from SnowflakeSnowflake
- LogicAlign and classify missing, orphaned, mismatched columns
- OutputOpen ClickUp reconciliation task per drifted tableClickUp
What it does
It keeps a source database and its warehouse replica structurally in sync. Each run it pulls the column list for every replicated table from both Postgres (the source) and Snowflake (the replica), aligns them by name, and reports three categories of drift: columns present in source but missing downstream, columns lingering in the replica after a source drop, and columns whose data type diverged. For each table with drift it opens a reconciliation task so an engineer fixes the pipeline mapping.
When to use it
Use it when a CDC or batch replication job mirrors operational tables into the warehouse and silent mapping gaps cause analytics to undercount or mistype fields. Run it daily to catch the slow accumulation of drift that replication tools don't always surface.
How it works
- 1A daily schedule starts the reconciler.
- 2Read source column definitions for the watched tables from Postgres.
- 3Read replica column definitions for the same tables from Snowflake.
- 4Align by table and column, then classify missing, orphaned, and type-mismatched fields.
- 5Branch: stop if fully in sync; otherwise continue per drifted table.
- 6Open a ClickUp reconciliation task itemizing each table's drift.
Set it up
What you configure once, before turning it on.
- 1Connect PostgresAny Postgres URL — query, write, migrate.
- 2Connect SnowflakeWarehouses, queries, shares.
- 3Connect ClickUpDocs + tasks + chats in one workspace.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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