DatriseAI-first ETL

Marketo Bulk to PostgreSQL Integration

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

How Datrise loads Marketo Bulk into PostgreSQL

Datrise syncs Marketo Bulk's leads, activities, program memberships, email events, lists, and custom objects into PostgreSQL as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.

Ideal for operational analytics and application backends that need fresh, queryable copies of your data.

Endpoints

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

PostgreSQL: Open-source relational database with strong SQL and extensions.

How Marketo Bulk entities map to PostgreSQL

Marketo Bulk entityPostgreSQL objectNotes
leadsmarketo_bulk_leadsid PK · custom fields → jsonb columns
activitiesmarketo_bulk_activitiestimestamptz events
program membershipsmarketo_bulk_program_membershipsid PK · linked to marketo_bulk_leads
email eventsmarketo_bulk_email_eventstimestamptz events

FAQ

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

Flexible values are stored as jsonb columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native PostgreSQL types.

How does the Marketo Bulk to PostgreSQL sync stay up to date?

It runs incrementally — Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

Early access

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