DatriseAI-first ETL

n8n to Microsoft SQL Server Integration

AI-first ETL from n8n into Microsoft SQL Server. Governed entities, incremental sync, typed landing tables.

How Datrise loads n8n into Microsoft SQL Server

Datrise syncs n8n's workflows, executions, nodes, credentials, execution logs, and triggers 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

n8n: Workflow automation across apps and APIs.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How n8n entities map to Microsoft SQL Server

n8n entityMicrosoft SQL Server objectNotes
workflowsn8n_workflowsid PK · custom fields → NVARCHAR(MAX) JSON columns
executionsn8n_executionsid PK · linked to n8n_workflows
nodesn8n_nodesid PK · linked to n8n_workflows
credentialsn8n_credentialsid PK · linked to n8n_workflows

FAQ

How does Datrise handle n8n'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 n8n 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

Early access

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