How to Use PostgreSQL Logical Replication for Warehouse CDC

May 2026

Postgres logical replication is most useful when the source replication design and the destination table contract are reviewed together.

Short Answer

Postgres logical replication is a strong CDC foundation because it exposes row changes directly from the database change log. The useful next step is making sure those changes flow into a destination contract the warehouse can trust.

That means publications, slots, keys, and delete semantics should be reviewed as part of one warehouse path, not scattered across separate setup guides.

Why Teams Struggle with This

Logical replication is often introduced as if source setup is the whole task. It is not. The source can be perfectly configured and the destination can still be confusing if the final-state design is weak.

• Replication slots and publications are configured without a clear downstream row-identity plan.
• Teams assume WAL capture guarantees a clean warehouse table by itself.
• Delete and replay handling are discussed too late.
• The first generated dbt models inherit uncertainty from the ingestion layer.

How Skippr Handles It

Skippr helps by putting the Postgres replication setup and the destination behavior in the same project. That shortens the distance between source mechanics and warehouse truth.

It also means the generated dbt project starts from an integration that has already been reasoned through, instead of one that still hides ingestion ambiguity.

• Postgres logical replication settings live next to the destination setup.
• Business keys are defined with the final-state table in mind.
• Bronze landing and dbt bootstrap stay on one execution path.
• The project is easier to review because source and warehouse assumptions are close together.

What the First Useful Version Looks Like

Logical replication is the transport layer. Warehouse trust comes from what you do with it.

That is the piece worth designing carefully.