Mailgun to Google BigQuery Integration

How Datrise loads Mailgun into Google BigQuery

Datrise syncs Mailgun's messages, domains, delivery events, bounces, complaints, and mailing lists into Google BigQuery as a partitioned table per source entity. Flexible or custom fields land in JSON or nested/repeated (STRUCT) columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.

Sync is incremental: Datrise uses appends to a staging table, then MERGE on stable id into the partitioned target, so re-runs update only what changed. Partition by ingestion or event date and cluster by entity id to keep scanned bytes low. BigQuery bills by bytes scanned, so Datrise partitions and clusters every table to keep query costs predictable.

Ideal for Google-stack analytics and ML on serverless infrastructure.

Endpoints

Mailgun: Transactional email API with delivery analytics.

Google BigQuery: Serverless analytics warehouse on GCP.

How Mailgun entities map to Google BigQuery

Mailgun entity	Google BigQuery object	Notes
messages	`mailgun_messages`	id PK · custom fields → JSON or nested/repeated (STRUCT) columns
domains	`mailgun_domains`	id PK · linked to mailgun_messages
delivery events	`mailgun_delivery_events`	TIMESTAMP events
bounces	`mailgun_bounces`	id PK · linked to mailgun_messages

FAQ

How does Datrise handle Mailgun's custom fields in Google BigQuery?

Flexible values are stored as JSON or nested/repeated (STRUCT) columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Google BigQuery types.

How does the Mailgun to Google BigQuery sync stay up to date?

It runs incrementally — Datrise uses appends to a staging table, then MERGE on stable id into the partitioned target.

Related pipelines

Early access

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