DatriseAI-first ETL

Zendesk Chat PlanetScale

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

How Datrise loads Zendesk Chat into PlanetScale

Datrise syncs Zendesk Chat's chats, agents, visitors, departments, and response times 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

Zendesk Chat: Live chat conversations and agent performance.

PlanetScale: Serverless MySQL platform with safe schema workflows.

How Zendesk Chat entities map to PlanetScale

Zendesk Chat entityPlanetScale objectNotes
chatszendesk_chat_chatsid PK · custom fields → JSON columns
agentszendesk_chat_agentsid PK · linked to zendesk_chat_chats
visitorszendesk_chat_visitorsid PK · linked to zendesk_chat_chats
departmentszendesk_chat_departmentsid PK · linked to zendesk_chat_chats

FAQ

How does Datrise handle Zendesk Chat'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 Zendesk Chat 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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