DatriseAI-first ETL

k6 Cloud to Apache Superset Integration

AI-first ETL from k6 Cloud into Apache Superset. Governed entities, incremental sync, typed landing tables.

How Datrise loads k6 Cloud into Apache Superset

Datrise syncs k6 Cloud's test runs, thresholds, checks, metrics, virtual users, and response times into Apache Superset as governed SQL tables Superset queries directly. Flexible or custom fields land in flattened columns for the explore UI, and timestamps such as created, updated, and status changes are typed as temporal columns for time-series charts.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned tables to keep dashboards responsive. Superset charts run live SQL, so Datrise lands query-friendly, indexed tables rather than wide raw payloads.

Ideal for open-source dashboards over your own database.

Endpoints

k6 Cloud: Load testing runs and performance thresholds.

Apache Superset: Open-source BI for SQL exploration, charts, and dashboard publishing.

How k6 Cloud entities map to Apache Superset

k6 Cloud entityApache Superset objectNotes
test runsk6_cloud_test_runsid PK · custom fields → flattened columns for the explore UI
thresholdsk6_cloud_thresholdsid PK · linked to k6_cloud_test_runs
checksk6_cloud_checksid PK · linked to k6_cloud_test_runs
metricsk6_cloud_metricsid PK · linked to k6_cloud_test_runs

FAQ

How does Datrise handle k6 Cloud's custom fields in Apache Superset?

Flexible values are stored as flattened columns for the explore UI, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Apache Superset types.

How does the k6 Cloud to Apache Superset sync stay up to date?

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

Related pipelines

Early access

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