DatriseAI-first ETL

Wrike to Domo Integration

AI-first ETL from Wrike into Domo. Governed entities, incremental sync, typed landing tables.

How Datrise loads Wrike into Domo

Datrise syncs Wrike's tasks, folders, projects, timelogs, custom fields, and task statuses into Domo as datasets in Domo's cloud store via connector. Flexible or custom fields land in flattened columns for Magic ETL, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses partitioned dataset updates rather than full replaces, so re-runs update only what changed. Domo dataset partitions keyed on load date. Domo stores its own copy of data, so Datrise sends incremental partitions to avoid re-uploading whole datasets.

Ideal for all-in-one cloud BI with built-in ETL.

Endpoints

Wrike: Project and task management with custom workflows.

Domo: Cloud BI platform combining data integration and executive dashboards.

How Wrike entities map to Domo

Wrike entityDomo objectNotes
taskswrike_tasksid PK · custom fields → flattened columns for Magic ETL
folderswrike_foldersid PK · linked to wrike_tasks
projectswrike_projectsid PK · linked to wrike_tasks
timelogswrike_timelogsid PK · linked to wrike_tasks

FAQ

How does Datrise handle Wrike's custom fields in Domo?

Flexible values are stored as flattened columns for Magic ETL, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Domo types.

How does the Wrike to Domo sync stay up to date?

It runs incrementally — Datrise uses partitioned dataset updates rather than full replaces.

Related pipelines

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