Log-Based CDC: Mechanics and Costs

Concepts covered: paCdc, paSchemaEvolution

Log-based CDC sounds free until the operational profile arrives. The mechanism is direct: the database is already writing every change to its log for crash recovery; tap the log, decode it, ship it downstream. The reality has costs. Replication slots can fill the disk. Schema changes upstream become Kafka topic problems. The CDC connector becomes a critical piece of infrastructure that must be operated like a database. Debezium and AWS DMS at a Glance The Replication Slot Problem Postgres uses logical replication slots to track which WAL position each consumer has reached. The slot guarantees the WAL is retained until the consumer confirms it has been read. That guarantee is also a liability. If the consumer falls behind or stops entirely, the WAL grows without bound on the source. A stuck

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This section is part of the Ingestion Patterns: Intermediate lesson on DataDriven, a free data engineering interview prep platform. Each section includes explanations, worked examples, and hands-on code challenges that execute in real time. SQL queries run against a live PostgreSQL database. Python runs in a sandboxed Docker container. Data modeling problems validate against interactive schema canvases. All content is framed around what data engineering interviewers actually test at companies like Meta, Google, Amazon, Netflix, Stripe, and Databricks.

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