Sailthru to Mode Integration
AI-first ETL from Sailthru into Mode. Governed entities, incremental sync, typed landing tables.
How Datrise loads Sailthru into Mode
Datrise syncs Sailthru's users, campaigns, blasts, message events, lists, and content items into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.
Ideal for SQL-first analysis with Python and R notebooks.
Endpoints
Sailthru: Personalized email and onsite content targeting.
Mode: Collaborative analytics workspace for SQL, Python, and shared reports.
How Sailthru entities map to Mode
| Sailthru entity | Mode object | Notes |
|---|---|---|
| users | sailthru_users | id PK · custom fields → flattened columns for SQL and notebooks |
| campaigns | sailthru_campaigns | id PK · linked to sailthru_users |
| blasts | sailthru_blasts | id PK · linked to sailthru_users |
| message events | sailthru_message_events | temporal columns events |
FAQ
How does Datrise handle Sailthru's custom fields in Mode?
Flexible values are stored as flattened columns for SQL and notebooks, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Mode types.
How does the Sailthru to Mode sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the queried tables.
Related pipelines
More destinations for Sailthru
Early access
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