Clockify to Holistics Integration
AI-first ETL from Clockify into Holistics. Governed entities, incremental sync, typed landing tables.
How Datrise loads Clockify into Holistics
Datrise syncs Clockify's time entries, projects, tasks, users, clients, and tags into Holistics as warehouse tables modeled in Holistics. Flexible or custom fields land in flattened columns for the modeling layer, and timestamps such as created, updated, and status changes are typed as date/time dimensions.
Sync is incremental: Datrise uses incremental refresh of the modeled tables, so re-runs update only what changed. Date-partitioned facts for fast aggregates. Holistics models data as code on top of SQL, so Datrise lands stable column names to keep your models from drifting.
Ideal for as-code BI modeling on a warehouse.
Endpoints
Clockify: Time tracking across projects and teams.
Holistics: Self-service BI with modeling layers and scheduled report delivery.
How Clockify entities map to Holistics
| Clockify entity | Holistics object | Notes |
|---|---|---|
| time entries | clockify_time_entries | id PK · custom fields → flattened columns for the modeling layer |
| 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 Holistics?
Flexible values are stored as flattened columns for the modeling layer, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Holistics types.
How does the Clockify to Holistics sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the modeled tables.
Related pipelines
More destinations for Clockify
Early access
Connect Clockify to Holistics the easy way
Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.