DatriseAI-first ETL

Postmark to Azure Data Lake Storage Integration

AI-first ETL from Postmark into Azure Data Lake Storage. Governed entities, incremental sync, typed landing tables.

How Datrise loads Postmark into Azure Data Lake Storage

Datrise syncs Postmark's messages, servers, delivery events, bounces, opens, and message streams into Azure Data Lake Storage as partitioned Parquet in ADLS Gen2 per source entity. Flexible or custom fields land in nested struct/map fields in Parquet, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.

Sync is incremental: Datrise uses writes new date partitions to the container and compacts on a schedule, so re-runs update only what changed. Hive-style partitioning by load date, readable by Synapse and Databricks. ADLS hierarchical namespace makes folder layout matter, so Datrise keeps a predictable entity/date path your Azure engines mount directly.

Ideal for Azure lakehouse storage shared across Synapse and Databricks.

Endpoints

Postmark: Transactional email delivery with detailed events.

Azure Data Lake Storage: ADLS Gen2 object storage for analytics workloads.

How Postmark entities map to Azure Data Lake Storage

Postmark entityAzure Data Lake Storage objectNotes
messagespostmark_app_messagesid PK · custom fields → nested struct/map fields in Parquet
serverspostmark_app_serversid PK · linked to postmark_app_messages
delivery eventspostmark_app_delivery_eventsISO-8601 timestamp columns events
bouncespostmark_app_bouncesid PK · linked to postmark_app_messages

FAQ

How does Datrise handle Postmark's custom fields in Azure Data Lake Storage?

Flexible values are stored as nested struct/map fields in Parquet, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Azure Data Lake Storage types.

How does the Postmark to Azure Data Lake Storage sync stay up to date?

It runs incrementally — Datrise uses writes new date partitions to the container and compacts on a schedule.

Related pipelines

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