Pivotal Tracker to Amazon Redshift Integration
AI-first ETL from Pivotal Tracker into Amazon Redshift. Governed entities, incremental sync, typed landing tables.
How Datrise loads Pivotal Tracker into Amazon Redshift
Datrise syncs Pivotal Tracker's stories, projects, iterations, epics, tasks, and story transitions into Amazon Redshift as a typed table per source entity. Flexible or custom fields land in SUPER columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMPTZ.
Sync is incremental: Datrise uses COPY from staged files, then a delete-and-insert merge on stable id, so re-runs update only what changed. A DISTKEY on the join id and a SORTKEY on the load timestamp. Redshift performance hinges on dist/sort keys, so Datrise picks them from your entity ids and sync timestamps rather than defaulting to EVEN distribution.
Ideal for AWS-native warehouses already using the Redshift ecosystem.
Endpoints
Pivotal Tracker: Agile story tracking and iteration planning.
Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.
How Pivotal Tracker entities map to Amazon Redshift
| Pivotal Tracker entity | Amazon Redshift object | Notes |
|---|---|---|
| stories | pivotal_tracker_stories | id PK · custom fields → SUPER columns |
| projects | pivotal_tracker_projects | id PK · linked to pivotal_tracker_stories |
| iterations | pivotal_tracker_iterations | id PK · linked to pivotal_tracker_stories |
| epics | pivotal_tracker_epics | id PK · linked to pivotal_tracker_stories |
FAQ
How does Datrise handle Pivotal Tracker's custom fields in Amazon Redshift?
Flexible values are stored as SUPER columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon Redshift types.
How does the Pivotal Tracker to Amazon Redshift sync stay up to date?
It runs incrementally — Datrise uses COPY from staged files, then a delete-and-insert merge on stable id.
Related pipelines
More destinations for Pivotal Tracker
- Pivotal Tracker → Databricks SQL Warehouse
- Pivotal Tracker → ClickHouse
- Pivotal Tracker → DuckDB
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- Pivotal Tracker → Azure Data Lake Storage
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- Pivotal Tracker → Spreadsheets
- Pivotal Tracker → Airtable
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- Pivotal Tracker → MongoDB
- Pivotal Tracker → Supabase
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Early access
Connect Pivotal Tracker to Amazon Redshift the easy way
Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.