Postmark to Holistics Integration
AI-first ETL from Postmark into Holistics. Governed entities, incremental sync, typed landing tables.
How Datrise loads Postmark into Holistics
Datrise syncs Postmark's messages, servers, delivery events, bounces, opens, and message streams into Holistics as warehouse tables modeled in Holistics. Flexible or custom fields land in flattened columns for the modeling layer, and timestamps such as created, updated, and status changes are typed as date/time dimensions.
Sync is incremental: Datrise uses incremental refresh of the modeled tables, so re-runs update only what changed. Date-partitioned facts for fast aggregates. Holistics models data as code on top of SQL, so Datrise lands stable column names to keep your models from drifting.
Ideal for as-code BI modeling on a warehouse.
Endpoints
Postmark: Transactional email delivery with detailed events.
Holistics: Self-service BI with modeling layers and scheduled report delivery.
How Postmark entities map to Holistics
| Postmark entity | Holistics object | Notes |
|---|---|---|
| messages | postmark_app_messages | id PK · custom fields → flattened columns for the modeling layer |
| servers | postmark_app_servers | id PK · linked to postmark_app_messages |
| delivery events | postmark_app_delivery_events | date/time dimensions events |
| bounces | postmark_app_bounces | id PK · linked to postmark_app_messages |
FAQ
How does Datrise handle Postmark's custom fields in Holistics?
Flexible values are stored as flattened columns for the modeling layer, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Holistics types.
How does the Postmark to Holistics sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the modeled tables.
Related pipelines
More destinations for Postmark
Early access
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