Logical replication: 2 real scaling case studies
2 of the 94 engineering write-ups in our database are tagged with the technique "logical replication". They come from 2 companies (Notion and Zalando) and were published between 2023 and 2025. Stack that shows up most often in these stories: PostgreSQL (2). 1 of the 2 state concrete scale numbers, for example "hundreds of event streams from Postgres" (Zalando). Each card below links to our short summary and the original post.
Contributing to Debezium: Fixing Logical Replication at Scale
Zalando's Fabric Event Streams provisions Debezium-in-embedded micro-apps so teams declare Postgres-sourced Kafka streams on Kubernetes; at peak the connectors handle hundreds of thousands of events per second across 100+ clusters, and have processed billions of events since 2018. Uncontrolled WAL growth on low-activity databases was the top operational issue until a pgjdbc keepalive flush advanced replication slots without table traffic. When newer Debezium hard-disabled that flush, Zalando contributed lsn.flush.mode (including connector_and_driver) and offset.mismatch.strategy (including trust_slot / trust_greater_lsn) so operators can opt into keepalive flushes while choosing whether the slot or the offset store wins on restart—both shipped in Debezium 3.4.0.Final.
The Great Re-shard: adding Postgres capacity (again) with zero downtime
Notion tripled its Postgres fleet by re-sharding with logical replication and careful PgBouncer cutovers, with no downtime.