Change Data Capture Pipeline with Debezium

Change Data Capture Pipeline with Debezium

Change Data Capture (CDC) reads a database's transaction log and emits each insert, update, and delete as an event, so downstream systems stay in sync without expensive full reloads or polling. Debezium is an open-source CDC platform built on Kafka Connect. This pipeline streams changes from operational databases into an analytics warehouse in near real time. Use it to keep analytics current, replicate across systems, or feed event-driven services without touching application code.

Components

• AWS RDS: the source operational databases (PostgreSQL, MySQL) with logical replication enabled.
• Debezium: source connectors that read the database write-ahead log and publish change events.
• AWS MSK: managed Kafka providing the durable event backbone.
• Kafka Connect: hosts Debezium source connectors and warehouse sink connectors.
• Schema Registry: stores Avro schemas so change-event structure evolves safely.
• Snowflake: the destination warehouse where changes are applied and history is retained.

Data Flow

Debezium connectors tail the transaction log of each source database and publish ordered change events to per-table Kafka topics, each carrying before and after row images. The schema registry validates event structure. A sink connector consumes the topics and applies changes to Snowflake, either as an append-only history table or as a merged current-state table. Because events preserve commit order per table, downstream state mirrors the source.

Scaling and Resilience

Throughput scales with topic partitions and Connect worker tasks. MSK replicates across availability zones so broker failures do not lose data. Debezium tracks log offsets so a restarted connector resumes exactly where it stopped, and initial snapshots backfill existing rows before switching to streaming. Kafka retention allows replay to rebuild a corrupted destination. Dead-letter queues capture poison records without halting the pipeline.

Security

Database replication users follow least privilege, granting only log-reading rights. Traffic uses TLS, and MSK enforces IAM or SASL authentication with topic ACLs. Snowflake connections use key-pair authentication and network policies. Sensitive columns can be masked or filtered in the connector configuration before events leave the source boundary.

Trade-offs and Alternatives

CDC delivers low-latency, low-impact replication, but it requires log access, careful handling of schema changes and large transactions, and operational care around snapshots. Managed alternatives include AWS DMS, Fivetran, or Airbyte, which trade flexibility for simpler setup. Periodic batch ELT is simpler but adds latency. Choose Debezium plus Kafka when you need open-source, real-time, replayable change streams that can fan out to many consumers beyond the warehouse.