DatriseAI-first ETL

Marketo Bulk to Apache Superset Integration

AI-first ETL from Marketo Bulk into Apache Superset. Governed entities, incremental sync, typed landing tables.

How Datrise loads Marketo Bulk into Apache Superset

Datrise syncs Marketo Bulk's leads, activities, program memberships, email events, lists, and custom objects into Apache Superset as governed SQL tables Superset queries directly. Flexible or custom fields land in flattened columns for the explore UI, and timestamps such as created, updated, and status changes are typed as temporal columns for time-series charts.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned tables to keep dashboards responsive. Superset charts run live SQL, so Datrise lands query-friendly, indexed tables rather than wide raw payloads.

Ideal for open-source dashboards over your own database.

Endpoints

Marketo Bulk: Bulk export of Marketo lead and activity history.

Apache Superset: Open-source BI for SQL exploration, charts, and dashboard publishing.

How Marketo Bulk entities map to Apache Superset

Marketo Bulk entityApache Superset objectNotes
leadsmarketo_bulk_leadsid PK · custom fields → flattened columns for the explore UI
activitiesmarketo_bulk_activitiestemporal columns for time-series charts events
program membershipsmarketo_bulk_program_membershipsid PK · linked to marketo_bulk_leads
email eventsmarketo_bulk_email_eventstemporal columns for time-series charts events

FAQ

How does Datrise handle Marketo Bulk's custom fields in Apache Superset?

Flexible values are stored as flattened columns for the explore UI, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Apache Superset types.

How does the Marketo Bulk to Apache Superset sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the queried tables.

Related pipelines

Early access

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