DatriseAI-first ETL

Aha to PostgreSQL Integration

AI-first ETL from Aha into PostgreSQL. Governed entities, incremental sync, typed landing tables.

How Datrise loads Aha into PostgreSQL

Datrise syncs Aha's features, releases, initiatives, ideas, goals, and epics into PostgreSQL as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.

Ideal for operational analytics and application backends that need fresh, queryable copies of your data.

Endpoints

Aha: Product roadmapping and release planning.

PostgreSQL: Open-source relational database with strong SQL and extensions.

How Aha entities map to PostgreSQL

Aha entityPostgreSQL objectNotes
featuresaha_featuresid PK · custom fields → jsonb columns
releasesaha_releasesid PK · linked to aha_features
initiativesaha_initiativesid PK · linked to aha_features
ideasaha_ideasid PK · linked to aha_features

FAQ

How does Datrise handle Aha's custom fields in PostgreSQL?

Flexible values are stored as jsonb columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native PostgreSQL types.

How does the Aha to PostgreSQL sync stay up to date?

It runs incrementally — Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

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