DatriseAI-first ETL

Wrike to Neon Integration

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

How Datrise loads Wrike into Neon

Datrise syncs Wrike's tasks, folders, projects, timelogs, custom fields, and task statuses into Neon as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative partitioning by load date. Neon separates compute from storage, so Datrise batches writes to keep autoscaling compute from cold-starting on every small change.

Ideal for serverless Postgres workloads that scale to zero between syncs.

Endpoints

Wrike: Project and task management with custom workflows.

Neon: Serverless Postgres destination with branching and autoscaling.

How Wrike entities map to Neon

Wrike entityNeon objectNotes
taskswrike_tasksid PK · custom fields → jsonb columns
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 Neon?

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

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

It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

Early access

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