DatriseAI-first ETL

Qualaroo to Databricks SQL Warehouse Integration

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

How Datrise loads Qualaroo into Databricks SQL Warehouse

Datrise syncs Qualaroo's surveys, responses, questions, respondents, nudges, and sentiment scores into Databricks SQL Warehouse as a Delta Lake table per source entity. Flexible or custom fields land in VARIANT or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.

Sync is incremental: Datrise uses a Delta MERGE on stable id, with change history available via time travel, so re-runs update only what changed. Delta partitioning by load date with OPTIMIZE/Z-ORDER on query keys. Datrise writes Unity Catalog–governed Delta tables, so lineage and permissions are managed centrally rather than per-notebook.

Ideal for lakehouse analytics and ML feature tables on Databricks.

Endpoints

Qualaroo: On-site surveys and user sentiment capture.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Qualaroo entities map to Databricks SQL Warehouse

Qualaroo entityDatabricks SQL Warehouse objectNotes
surveysqualaroo_surveysid PK · custom fields → VARIANT or STRUCT columns
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 Databricks SQL Warehouse?

Flexible values are stored as VARIANT or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Databricks SQL Warehouse types.

How does the Qualaroo to Databricks SQL Warehouse sync stay up to date?

It runs incrementally — Datrise uses a Delta MERGE on stable id, with change history available via time travel.

Related pipelines

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