Clockify to Klipfolio Integration
AI-first ETL from Clockify into Klipfolio. Governed entities, incremental sync, typed landing tables.
How Datrise loads Clockify into Klipfolio
Datrise syncs Clockify's time entries, projects, tasks, users, clients, and tags into Klipfolio as query-ready tables or feeds Klipfolio reads. Flexible or custom fields land in flattened columns for Klips, and timestamps such as created, updated, and status changes are typed as date/time columns.
Sync is incremental: Datrise uses incremental refresh of the connected tables or data feeds, so re-runs update only what changed. Date-partitioned facts for trend Klips. Klipfolio pulls from sources on a refresh interval, so Datrise keeps tables incrementally current to match.
Ideal for real-time KPI dashboards and wallboards.
Endpoints
Clockify: Time tracking across projects and teams.
Klipfolio: Dashboard platform for real-time KPIs and metric wallboards.
How Clockify entities map to Klipfolio
| Clockify entity | Klipfolio object | Notes |
|---|---|---|
| time entries | clockify_time_entries | id PK · custom fields → flattened columns for Klips |
| 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 Klipfolio?
Flexible values are stored as flattened columns for Klips, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Klipfolio types.
How does the Clockify to Klipfolio sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables or data feeds.
Related pipelines
More destinations for Clockify
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