DatriseAI-first ETL

Heroku to Redash Integration

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

How Datrise loads Heroku into Redash

Datrise syncs Heroku's apps, dynos, releases, add-ons, config vars, and build logs 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

Heroku: Application platform with dynos and add-ons.

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

How Heroku entities map to Redash

Heroku entityRedash objectNotes
appsheroku_appsid PK · custom fields → flattened columns for query results
dynosheroku_dynosid PK · linked to heroku_apps
releasesheroku_releasesid PK · linked to heroku_apps
add-onsheroku_add_onsid PK · linked to heroku_apps

FAQ

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

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

Related pipelines

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