Kafka Connect vs Debezium

Kafka Connect and Debezium are not competitors — they are complementary. Kafka Connect is the framework; Debezium is a set of connectors that run on it. However, the comparison matters because teams often choose between Debezium's CDC connectors and Kafka Connect's JDBC source connector.

Framework vs Connectors

Kafka Connect is a distributed data integration framework. It runs source connectors (that pull data into Kafka) and sink connectors (that push data from Kafka to external systems). It handles scaling, offset management, and fault tolerance.

Debezium provides source connectors for change data capture — reading database transaction logs (PostgreSQL WAL, MySQL binlog, MongoDB oplog) and producing change events into Kafka topics.

JDBC Polling vs Log-Based CDC

The JDBC source connector polls a database table on a schedule, selecting rows where a timestamp or incrementing column has changed. This approach:

• Misses deletes (no row to select)
• Misses intermediate updates between polls
• Adds query load to the source database
• Has inherent latency (polling interval)

Debezium reads the database's transaction log directly:

• Captures every change including deletes
• Near-zero latency (events produced as transactions commit)
• Minimal database impact (log reading is lightweight)
• Captures schema changes automatically

When JDBC Is Sufficient

For tables that are append-only (logs, events, audit trails), the JDBC connector works fine. Rows are only inserted, never updated or deleted, so nothing is missed.

Debezium Beyond Kafka Connect

Debezium Server can run standalone without Kafka Connect, streaming changes directly to other systems (Pulsar, Kinesis, Google Pub/Sub). This decouples CDC from the Kafka ecosystem when needed. See our system design interview guide and CDC concepts for architectural patterns.