DatriseAI-first ETL

Wrike to Microsoft SQL Server Integration

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

How Datrise loads Wrike into Microsoft SQL Server

Datrise syncs Wrike's tasks, folders, projects, timelogs, custom fields, and task statuses into Microsoft SQL Server as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.

Sync is incremental: Datrise uses a watermark on updated-at, applied with a MERGE statement, so re-runs update only what changed. Optional partitioned tables on a date partition function. SQL Server defaults to a case-insensitive collation, so Datrise preserves original casing in a metadata column to avoid silent key collisions.

Ideal for Microsoft-stack analytics and Power BI Import models.

Endpoints

Wrike: Project and task management with custom workflows.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Wrike entities map to Microsoft SQL Server

Wrike entityMicrosoft SQL Server objectNotes
taskswrike_tasksid PK · custom fields → NVARCHAR(MAX) JSON 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 Microsoft SQL Server?

Flexible values are stored as NVARCHAR(MAX) JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Microsoft SQL Server types.

How does the Wrike to Microsoft SQL Server sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with a MERGE statement.

Related pipelines

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