ClickUp → Mode
AI-first ETL from ClickUp into Mode. Governed entities, incremental sync, typed landing tables.
How Datrise loads ClickUp into Mode
Datrise syncs ClickUp's tasks, custom fields, statuses, docs, and workspace execution data into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.
Ideal for SQL-first analysis with Python and R notebooks.
Endpoints
ClickUp: Work management platform for tasks, docs, and operations.
Mode: Collaborative analytics workspace for SQL, Python, and shared reports.
How ClickUp entities map to Mode
| ClickUp entity | Mode object | Notes |
|---|---|---|
| tasks | clickup_tasks | id PK · custom fields → flattened columns for SQL and notebooks |
| custom fields | clickup_custom_fields | id PK · linked to clickup_tasks |
| statuses | clickup_statuses | temporal columns events |
| docs | clickup_docs | id PK · linked to clickup_tasks |
FAQ
How does Datrise handle ClickUp's custom fields in Mode?
Flexible values are stored as flattened columns for SQL and notebooks, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Mode types.
How does the ClickUp to Mode sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the queried tables.
Related pipelines
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