SparkPost to Holistics Integration

How Datrise loads SparkPost into Holistics

Datrise syncs SparkPost's messages, transmissions, delivery events, bounces, suppressions, and sending domains 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

SparkPost: Transactional email delivery and deliverability metrics.

Holistics: Self-service BI with modeling layers and scheduled report delivery.

How SparkPost entities map to Holistics

SparkPost entity	Holistics object	Notes
messages	`sparkpost_messages`	id PK · custom fields → flattened columns for the modeling layer
transmissions	`sparkpost_transmissions`	id PK · linked to sparkpost_messages
delivery events	`sparkpost_delivery_events`	date/time dimensions events
bounces	`sparkpost_bounces`	id PK · linked to sparkpost_messages

FAQ

How does Datrise handle SparkPost'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 SparkPost to Holistics sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the modeled tables.

Related pipelines

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