Everhour to Klipfolio Integration
AI-first ETL from Everhour into Klipfolio. Governed entities, incremental sync, typed landing tables.
How Datrise loads Everhour into Klipfolio
Datrise syncs Everhour's time entries, projects, tasks, users, clients, and budgets 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
Everhour: Time tracking and budgets for project teams.
Klipfolio: Dashboard platform for real-time KPIs and metric wallboards.
How Everhour entities map to Klipfolio
| Everhour entity | Klipfolio object | Notes |
|---|---|---|
| time entries | everhour_time_entries | id PK · custom fields → flattened columns for Klips |
| projects | everhour_projects | id PK · linked to everhour_time_entries |
| tasks | everhour_tasks | id PK · linked to everhour_time_entries |
| users | everhour_users | id PK · linked to everhour_time_entries |
FAQ
How does Datrise handle Everhour'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 Everhour to Klipfolio sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables or data feeds.
Related pipelines
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