DatriseAI-first ETL

Segment PlanetScale

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

How Datrise loads Segment into PlanetScale

Datrise syncs Segment's sources, destinations, track events, identify calls, and schema catalog 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

Segment: Customer data platform routing events to warehouses.

PlanetScale: Serverless MySQL platform with safe schema workflows.

How Segment entities map to PlanetScale

Segment entityPlanetScale objectNotes
sourcessegment_sourcesid PK · custom fields → JSON columns
destinationssegment_destinationsid PK · linked to segment_sources
track eventssegment_track_eventsDATETIME events
identify callssegment_identify_callsid PK · linked to segment_sources

FAQ

How does Datrise handle Segment'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 Segment 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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