SparkPost to Domo Integration

How Datrise loads SparkPost into Domo

Datrise syncs SparkPost's messages, transmissions, delivery events, bounces, suppressions, and sending domains into Domo as datasets in Domo's cloud store via connector. Flexible or custom fields land in flattened columns for Magic ETL, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses partitioned dataset updates rather than full replaces, so re-runs update only what changed. Domo dataset partitions keyed on load date. Domo stores its own copy of data, so Datrise sends incremental partitions to avoid re-uploading whole datasets.

Ideal for all-in-one cloud BI with built-in ETL.

Endpoints

SparkPost: Transactional email delivery and deliverability metrics.

Domo: Cloud BI platform combining data integration and executive dashboards.

How SparkPost entities map to Domo

SparkPost entity	Domo object	Notes
messages	`sparkpost_messages`	id PK · custom fields → flattened columns for Magic ETL
transmissions	`sparkpost_transmissions`	id PK · linked to sparkpost_messages
delivery events	`sparkpost_delivery_events`	date/time columns events
bounces	`sparkpost_bounces`	id PK · linked to sparkpost_messages

FAQ

How does Datrise handle SparkPost's custom fields in Domo?

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

How does the SparkPost to Domo sync stay up to date?

It runs incrementally — Datrise uses partitioned dataset updates rather than full replaces.

Related pipelines

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