DatriseAI-first ETL

Pagerduty to PlanetScale Integration

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

How Datrise loads Pagerduty into PlanetScale

Datrise syncs Pagerduty's incidents, services, schedules, escalation policies, log entries, and responders 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

Pagerduty: Incident response, on-call schedules, and escalation.

PlanetScale: Serverless MySQL platform with safe schema workflows.

How Pagerduty entities map to PlanetScale

Pagerduty entityPlanetScale objectNotes
incidentspagerduty_incidentsid PK · custom fields → JSON columns
servicespagerduty_servicesid PK · linked to pagerduty_incidents
schedulespagerduty_schedulesid PK · linked to pagerduty_incidents
escalation policiespagerduty_escalation_policiesid PK · linked to pagerduty_incidents

FAQ

How does Datrise handle Pagerduty'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 Pagerduty 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

Early access

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