DatriseAI-first ETL

Shopify Byoa PlanetScale

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

How Datrise loads Shopify Byoa into PlanetScale

Datrise syncs Shopify Byoa'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

Shopify Byoa: SaaS or API data source for analytics and warehouse sync.

PlanetScale: Serverless MySQL platform with safe schema workflows.

How Shopify Byoa entities map to PlanetScale

Shopify Byoa entityPlanetScale objectNotes
recordsshopify_byoa_recordsid PK · custom fields → JSON columns
eventsshopify_byoa_eventsDATETIME events
configuration objectsshopify_byoa_configuration_objectsid PK · linked to shopify_byoa_records

FAQ

How does Datrise handle Shopify Byoa'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 Shopify Byoa 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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