DatriseAI-first ETL

Postmark App PostgreSQL

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

How Datrise loads Postmark App into PostgreSQL

Datrise syncs Postmark App's records, events, and configuration objects 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

Postmark App: SaaS or API data source for analytics and warehouse sync.

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

How Postmark App entities map to PostgreSQL

Postmark App entityPostgreSQL objectNotes
recordspostmark_app_recordsid PK · custom fields → jsonb columns
eventspostmark_app_eventstimestamptz events
configuration objectspostmark_app_configuration_objectsid PK · linked to postmark_app_records

FAQ

How does Datrise handle Postmark App'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 Postmark App 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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