Clockify to PlanetScale Integration
AI-first ETL from Clockify into PlanetScale. Governed entities, incremental sync, typed landing tables.
How Datrise loads Clockify into PlanetScale
Datrise syncs Clockify's time entries, projects, tasks, users, clients, and tags 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
Clockify: Time tracking across projects and teams.
PlanetScale: Serverless MySQL platform with safe schema workflows.
How Clockify entities map to PlanetScale
| Clockify entity | PlanetScale object | Notes |
|---|---|---|
| time entries | clockify_time_entries | id PK · custom fields → JSON columns |
| projects | clockify_projects | id PK · linked to clockify_time_entries |
| tasks | clockify_tasks | id PK · linked to clockify_time_entries |
| users | clockify_users | id PK · linked to clockify_time_entries |
FAQ
How does Datrise handle Clockify'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 Clockify 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 Clockify
More sources for PlanetScale
Early access
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