Asana → PlanetScale
AI-first ETL from Asana into PlanetScale. Governed entities, incremental sync, typed landing tables.
How Datrise loads Asana into PlanetScale
Datrise syncs Asana's projects, tasks, sections, custom fields, and assignment timelines 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
Asana: Work management for projects, tasks, and cross-team delivery.
PlanetScale: Serverless MySQL platform with safe schema workflows.
How Asana entities map to PlanetScale
| Asana entity | PlanetScale object | Notes |
|---|---|---|
| projects | asana_projects | id PK · custom fields → JSON columns |
| tasks | asana_tasks | id PK · linked to asana_projects |
| sections | asana_sections | id PK · linked to asana_projects |
| custom fields | asana_custom_fields | id PK · linked to asana_projects |
FAQ
How does Datrise handle Asana'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 Asana 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
More destinations for Asana
More sources for PlanetScale
Early access
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