DatriseAI-first ETL

Qualaroo to Redash Integration

AI-first ETL from Qualaroo into Redash. Governed entities, incremental sync, typed landing tables.

How Datrise loads Qualaroo into Redash

Datrise syncs Qualaroo's surveys, responses, questions, respondents, nudges, and sentiment scores 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

Qualaroo: On-site surveys and user sentiment capture.

Redash: Open-source SQL client for queries, visualizations, and dashboards.

How Qualaroo entities map to Redash

Qualaroo entityRedash objectNotes
surveysqualaroo_surveysid PK · custom fields → flattened columns for query results
responsesqualaroo_responsesid PK · linked to qualaroo_surveys
questionsqualaroo_questionsid PK · linked to qualaroo_surveys
respondentsqualaroo_respondentsid PK · linked to qualaroo_surveys

FAQ

How does Datrise handle Qualaroo'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 Qualaroo to Redash sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

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