DatriseAI-first ETL

Harness to Apache Superset Integration

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

How Datrise loads Harness into Apache Superset

Datrise syncs Harness's pipelines, deployments, services, environments, execution logs, and approvals 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

Harness: Continuous delivery pipelines and deployment verification.

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

How Harness entities map to Apache Superset

Harness entityApache Superset objectNotes
pipelinesharness_pipelinesid PK · custom fields → flattened columns for the explore UI
deploymentsharness_deploymentsid PK · linked to harness_pipelines
servicesharness_servicesid PK · linked to harness_pipelines
environmentsharness_environmentsid PK · linked to harness_pipelines

FAQ

How does Datrise handle Harness'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 Harness 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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