Retently to Redash Integration
AI-first ETL from Retently into Redash. Governed entities, incremental sync, typed landing tables.
How Datrise loads Retently into Redash
Datrise syncs Retently's surveys, responses, customers, NPS scores, campaigns, and feedback comments 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
Retently: NPS and customer satisfaction survey tracking.
Redash: Open-source SQL client for queries, visualizations, and dashboards.
How Retently entities map to Redash
| Retently entity | Redash object | Notes |
|---|---|---|
| surveys | retently_surveys | id PK · custom fields → flattened columns for query results |
| responses | retently_responses | id PK · linked to retently_surveys |
| customers | retently_customers | id PK · linked to retently_surveys |
| NPS scores | retently_nps_scores | id PK · linked to retently_surveys |
FAQ
How does Datrise handle Retently'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 Retently to Redash sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for Retently
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