DatriseAI-first ETL

Pivotal Tracker to Metabase Integration

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

How Datrise loads Pivotal Tracker into Metabase

Datrise syncs Pivotal Tracker's stories, projects, iterations, epics, tasks, and story transitions 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

Pivotal Tracker: Agile story tracking and iteration planning.

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

How Pivotal Tracker entities map to Metabase

Pivotal Tracker entityMetabase objectNotes
storiespivotal_tracker_storiesid PK · custom fields → flattened columns for the question builder
projectspivotal_tracker_projectsid PK · linked to pivotal_tracker_stories
iterationspivotal_tracker_iterationsid PK · linked to pivotal_tracker_stories
epicspivotal_tracker_epicsid PK · linked to pivotal_tracker_stories

FAQ

How does Datrise handle Pivotal Tracker'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 Pivotal Tracker 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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