Stream every database change.

No. Etlworks's CDC engine is built in and runs inside the platform. It uses the same Debezium-compatible binlog reading approach but doesn't require a separate Debezium installation, Kafka cluster, or schema registry. If you already use Kafka, you can publish CDC events to it as a destination, but it is not a prerequisite.

Sub-second in most production deployments. Actual latency depends on source database load, network, and destination throughput, but the engine itself processes change events as they're emitted by the database log. Lag metrics are visible per-pipeline in monitoring.

Schema evolution is automatic for additive changes (new columns, larger types). Destructive changes (dropped columns, incompatible type changes) trigger a pipeline alert and require explicit confirmation before propagating. Schema history is retained for audit.

Yes. The hybrid agent runs inside your network, reads the database log locally, and connects to the destination itself, so change events go straight from your network into Snowflake, BigQuery or Redshift rather than passing through Etlworks. The agent’s only connection to us is outbound HTTPS on 443 for configuration and monitoring, so there are no inbound ports and no VPN. If you would rather the warehouse load ran from the cloud side, the agent can stage the data in cloud storage instead and a separate flow loads it from there. Both patterns run in production at petabyte scale.

CDC pipelines persist offsets and resume from the last committed position. Source database log retention is the only constraint: as long as the log is still available, no events are lost. Default retention is 7 days; configurable per source.

Etlworks's CDC engine is Debezium-compatible at the protocol level, with the same binlog-reading approach and the same change event format. The differences: it runs inside Etlworks (no separate Kafka Connect / Zookeeper / schema registry), includes a managed UI, supports transformations and routing in the same pipeline, and includes destinations beyond Kafka topics (warehouses, files, APIs). If you need raw Debezium to fan out to many Kafka consumers, use raw Debezium. If you want the capture, the destinations, and the transformations in one place, that is what this is.

Etlworks pricing is per-tier, not per-row or per-event. CDC throughput is included in every paid plan. High-volume customers (hundreds of millions of changes per day) typically run on Enterprise plans for HA and dedicated support, but there's no per-event surcharge.