Marketo Bulk to DuckDB Integration

How Datrise loads Marketo Bulk into DuckDB

Datrise syncs Marketo Bulk's leads, activities, program memberships, email events, lists, and custom objects into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.

Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.

Ideal for local and notebook analytics without standing up a server.

Endpoints

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

DuckDB: In-process analytics database for fast local OLAP.

How Marketo Bulk entities map to DuckDB

Marketo Bulk entity	DuckDB object	Notes
leads	`marketo_bulk_leads`	id PK · custom fields → JSON or STRUCT columns
activities	`marketo_bulk_activities`	TIMESTAMP WITH TIME ZONE events
program memberships	`marketo_bulk_program_memberships`	id PK · linked to marketo_bulk_leads
email events	`marketo_bulk_email_events`	TIMESTAMP WITH TIME ZONE events

FAQ

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

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

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

It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.

Related pipelines

Early access

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