DatriseAI-first ETL

Sailthru Domo

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

How Datrise loads Sailthru into Domo

Datrise syncs Sailthru's records, events, and configuration objects 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

Sailthru: SaaS or API data source for analytics and warehouse sync.

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

How Sailthru entities map to Domo

Sailthru entityDomo objectNotes
recordssailthru_recordsid PK · custom fields → flattened columns for Magic ETL
eventssailthru_eventsdate/time columns events
configuration objectssailthru_configuration_objectsid PK · linked to sailthru_records

FAQ

How does Datrise handle Sailthru'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 Sailthru 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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