DatriseAI-first ETL

Marketo Bulk PlanetScale

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

How Datrise loads Marketo Bulk into PlanetScale

Datrise syncs Marketo Bulk's records, events, and configuration objects into PlanetScale as a typed table per source entity. Flexible or custom fields land in JSON columns, and timestamps such as created, updated, and status changes are typed as DATETIME.

Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE, so re-runs update only what changed. Vitess sharding by tenant or entity key for very large tables. PlanetScale disallows foreign-key constraints by default, so Datrise models relationships by stable id columns rather than enforced FKs.

Ideal for horizontally scalable MySQL apps on Vitess.

Endpoints

Marketo Bulk: SaaS or API data source for analytics and warehouse sync.

PlanetScale: Serverless MySQL platform with safe schema workflows.

How Marketo Bulk entities map to PlanetScale

Marketo Bulk entityPlanetScale objectNotes
recordsmarketo_bulk_recordsid PK · custom fields → JSON columns
eventsmarketo_bulk_eventsDATETIME events
configuration objectsmarketo_bulk_configuration_objectsid PK · linked to marketo_bulk_records

FAQ

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

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

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

It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE.

Related pipelines

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