Data CDC Tool

The Data CDC Tool captures changes between data snapshots to enable reliable change data capture (CDC) workflows and incremental loading for data warehouses and lakes. It is designed for data engineers, DBAs, and governance teams who need auditable deltas and reproducible data pipelines.
Conceptually, it monitors row-level state, compares new snapshots against the last checkpoint, and emits only the changed rows or a change log indicating inserts, updates, or deletes. When CDC logs exist in the source, the tool consumes them to minimize load; when not, it uses efficient snapshot diffing and primary-key-based reconciliation.
Benefit: accurate reconciliation across pipelines, reduced data transfer, and a verifiable audit trail. Differentiators include multi-source support, schema drift detection, and flexible export targets (JSON, Parquet, or streaming destinations). It suits analytics, data warehouse maintenance, and data governance use cases.
Core features include: table selection, time-window configuration, delta export, delta summaries, and error handling. Typical workflows involve connecting to a CDC-enabled source, selecting tables, setting since/until, running the delta, and routing outputs to downstream systems.