Streaming database change replication with Debezium and Kafka

I build change data capture (CDC) pipelines that turn your database into a live event stream so all other systems stay current without nightly batch exports and fragile export scripts. Using Debezium and Kafka, I connect directly to the transaction log of the primary store and capture every insert, update, and delete the moment it commits. Your application keeps writing to one database exactly as it does now, and I invisibly deliver those changes wherever they're needed. No one manually updates data, and you never wake up to a stale dashboard or search index lagging reality by hours.

My work covers the whole path from source to sink. I set up the right Debezium connector for your engine — PostgreSQL, MySQL, SQL Server, MongoDB, or Oracle — and fine-tune the initial snapshot, offset storage, and connector restart so failure never means lost or doubled events. I handle schema evolution through a schema registry so a new column or renamed field reaches consumers cleanly, not breaking them. On the delivery side I connect the stream to search clusters, caches, data warehouses, and other microservices, designing exactly-once semantics where correctness matters and idempotent upsert operations everywhere else.

You get a documented, observable pipeline with lag metrics, dead-letter handling, and alerts, plus clear procedures for the failures that actually happen in prod. I'll help replay history when you need to rebuild a sink from scratch, because good CDC is not just a stream but a rewindable log of everything that ever changed. Name the source database and where data should land, and I'll make your systems sync themselves.

— Debezium connector setup, snapshots, and offsets
— Schema registry and safe schema evolution
— Exactly-once and idempotent delivery to search, cache, and warehouse
— Lag monitoring, dead-letter queues, and history replay