DatriseAI-first ETL

Sailthru to Amazon QuickSight Integration

AI-first ETL from Sailthru into Amazon QuickSight. Governed entities, incremental sync, typed landing tables.

How Datrise loads Sailthru into Amazon QuickSight

Datrise syncs Sailthru's users, campaigns, blasts, message events, lists, and content items into Amazon QuickSight as warehouse tables or a SPICE-loaded dataset. Flexible or custom fields land in flattened columns for analyses, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind SPICE or direct query, so re-runs update only what changed. Date-partitioned facts to bound SPICE refresh. QuickSight SPICE is an in-memory copy, so Datrise keeps the backing tables incremental so refreshes stay cheap.

Ideal for AWS-native dashboards with pay-per-session pricing.

Endpoints

Sailthru: Personalized email and onsite content targeting.

Amazon QuickSight: AWS serverless BI with SPICE and embedded analytics.

How Sailthru entities map to Amazon QuickSight

Sailthru entityAmazon QuickSight objectNotes
userssailthru_usersid PK · custom fields → flattened columns for analyses
campaignssailthru_campaignsid PK · linked to sailthru_users
blastssailthru_blastsid PK · linked to sailthru_users
message eventssailthru_message_eventsdate/time fields events

FAQ

How does Datrise handle Sailthru's custom fields in Amazon QuickSight?

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

How does the Sailthru to Amazon QuickSight sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind SPICE or direct query.

Related pipelines

Early access

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