Orchestration + trust

Airflow integrations that catch silent failures

Keep Airflow as your orchestrator. Add a catalog, lineage, and checks so green DAGs still mean trustworthy data.

What “Airflow integration” should mean

Most teams searching for Airflow integrations already run DAGs. They need metadata, quality, and lineage that stay aligned with those DAGs — not another scheduler.

DataXPipe integrates by importing DAG structure into a pipeline catalog, recording check results against runs, and sharing Passports when data meets SLA.

Integration surfaces

DAG import

Bootstrap pipeline identity, edges, and owners from existing DAGs.

Run + check linkage

Freshness and KPI results post with the orchestrator run ID.

CI before merge

PR blast-radius preview when specs or contracts change.

Alerts

Slack or email when checks fail — even if Airflow stayed green.

Passports

Shareable trust warrants that revoke on silent failure.

Lineage graph

See downstream dashboards and contracts at risk.

Get integrated in three steps

  1. 01

    Import the DAG

    Paste or upload DAG source in guided setup.

  2. 02

    Attach checks

    Freshness on the marts execs actually open.

  3. 03

    Share a Passport

    Prove the pipeline is trustworthy — not just green.

Airflow integrations FAQ

Orchestration success vs data trust.

What Airflow integrations does DataXPipe support?+

Import DAG source to bootstrap the catalog and lineage, generate or notify on runs so check results attach to executions, and use CI impact analysis before DAG/spec changes merge. You do not replace Airflow — you add trust on top.

Does DataXPipe replace Airflow?+

No. Airflow remains the orchestrator. DataXPipe is the pipeline catalog and trust runtime: specs, lineage, freshness/KPI checks, Passports, and consumer contracts.

Why add anything if Airflow already shows green?+

Task success means the operator finished without an exception. It does not prove the mart is fresh, non-empty, or within KPI baselines. That gap is a silent failure — the #1 reason teams add dataset checks beside Airflow.

Connect Airflow to your catalog

Import a DAG, attach freshness checks, and issue a Pipeline Passport — free for two pipelines.