DatriseAI-first ETL

Heroku to Metabase Integration

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

How Datrise loads Heroku into Metabase

Datrise syncs Heroku's apps, dynos, releases, add-ons, config vars, and build logs into Metabase as clean SQL tables Metabase auto-discovers. Flexible or custom fields land in flattened columns for the question builder, and timestamps such as created, updated, and status changes are typed as temporal columns for trends.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for large questions. Metabase auto-scans schemas, so Datrise uses readable table and column names so the no-code UI stays self-explanatory.

Ideal for self-serve questions and dashboards for whole teams.

Endpoints

Heroku: Application platform with dynos and add-ons.

Metabase: Open-source analytics with questions, dashboards, and embedded insights.

How Heroku entities map to Metabase

Heroku entityMetabase objectNotes
appsheroku_appsid PK · custom fields → flattened columns for the question builder
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 Metabase?

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

How does the Heroku to Metabase sync stay up to date?

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

Related pipelines

Early access

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