n8n to Redash Integration
AI-first ETL from n8n into Redash. Governed entities, incremental sync, typed landing tables.
How Datrise loads n8n into Redash
Datrise syncs n8n's workflows, executions, nodes, credentials, execution logs, and triggers into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.
Ideal for lightweight, query-driven dashboards.
Endpoints
n8n: Workflow automation across apps and APIs.
Redash: Open-source SQL client for queries, visualizations, and dashboards.
How n8n entities map to Redash
| n8n entity | Redash object | Notes |
|---|---|---|
| workflows | n8n_workflows | id PK · custom fields → flattened columns for query results |
| executions | n8n_executions | id PK · linked to n8n_workflows |
| nodes | n8n_nodes | id PK · linked to n8n_workflows |
| credentials | n8n_credentials | id PK · linked to n8n_workflows |
FAQ
How does Datrise handle n8n's custom fields in Redash?
Flexible values are stored as flattened columns for query results, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Redash types.
How does the n8n to Redash sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for n8n
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