DatriseAI-first ETL

Clockify to Spreadsheets Integration

AI-first ETL from Clockify into Spreadsheets. Governed entities, incremental sync, typed landing tables.

How Datrise loads Clockify into Spreadsheets

Datrise syncs Clockify's time entries, projects, tasks, users, clients, and tags into Spreadsheets as a tab per source entity. Flexible or custom fields land in JSON-stringified cells for nested fields, and timestamps such as created, updated, and status changes are typed as ISO-8601 text or serial date cells.

Sync is incremental: Datrise uses refreshes the tab's rows each run, preserving header order, so re-runs update only what changed. Sheets caps out around the low millions of cells, so Datrise lands a curated column set rather than every raw field.

Ideal for lightweight, shareable reporting for non-technical teams.

Endpoints

Clockify: Time tracking across projects and teams.

Spreadsheets: Business-friendly spreadsheet destination for collaborative analysis.

How Clockify entities map to Spreadsheets

Clockify entitySpreadsheets objectNotes
time entriesclockify_time_entriesid PK · custom fields → JSON-stringified cells for nested fields
projectsclockify_projectsid PK · linked to clockify_time_entries
tasksclockify_tasksid PK · linked to clockify_time_entries
usersclockify_usersid PK · linked to clockify_time_entries

FAQ

How does Datrise handle Clockify's custom fields in Spreadsheets?

Flexible values are stored as JSON-stringified cells for nested fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Spreadsheets types.

How does the Clockify to Spreadsheets sync stay up to date?

It runs incrementally — Datrise uses refreshes the tab's rows each run, preserving header order.

Related pipelines

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