A pattern for streaming row-level changes (inserts, updates, deletes) from a source database to downstream systems in near-real-time — typically by tailing the database's write-ahead log.
CDC reads database transaction logs (Postgres WAL, MySQL binlog, SQL Server Change Tracking) and produces a stream of change events. Downstream consumers can use these to keep replicas in sync, populate data warehouses (Snowflake, BigQuery via Fivetran/Airbyte), invalidate caches, or trigger workflows. CDC is dramatically cheaper than periodic full-table scans for large tables — only the deltas move. Debezium is the leading open-source CDC engine; many SaaS pipelines (Fivetran, Airbyte) use CDC under the hood.
Streaming Postgres WAL changes via Debezium to Kafka, then into Snowflake — sub-minute analytics lag instead of hourly batch updates.
CDC is how modern data stacks achieve near-real-time analytics without overloading source databases — every architecture team handling > 10GB of transactional data should know it.
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