Estuary vs Fivetran: PostgreSQL CDC Tested in Real Time

What actually changes when you run PostgreSQL CDC through Estuary instead of Fivetran? In this sponsored hands-on comparison, we run the same PostgreSQL-to-warehouse pipeline through both architectures and look at three things that matter in production: How quickly inserts, updates, and deletes reach the destination How multi-table transactions are delivered What happens when you add a second destination You’ll see PostgreSQL logical replication and WAL-based CDC in action, including a live delete test, transaction consistency, backfills, and multi-destination fan-out. We also break down an important architectural difference: Fivetran uses point-to-point source-to-destination connections, while Estuary captures changes once into durable collections that can be materialized to multiple destinations independently. The video also covers how the two pricing models differ, including Fivetran’s Monthly Active Rows (MAR) model and Estuary’s usage-based data-movement pricing. What we cover 00:00 PostgreSQL CDC delete race 01:00 Pipeline architecture and test setup 02:30 CDC freshness and latency 03:00 Inserts, updates, and deletes 04:00 Transaction consistency 06:00 Estuary collections explained 07:00 Adding a second destination 09:30 Estuary vs Fivetran pricing models 12:30 When Fivetran still makes sense 13:30 Try the PostgreSQL CDC pipeline yourself #PostgreSQL #CDC #DataEngineering