Smaily to Birst Integration
AI-first ETL from Smaily into Birst. Governed entities, incremental sync, typed landing tables.
How Datrise loads Smaily into Birst
Datrise syncs Smaily's subscribers, campaigns, lists, autoresponders, email events, and segments into Birst as warehouse tables for Birst's automated star schema. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.
Sync is incremental: Datrise uses incremental refresh of the source tables Birst ingests, so re-runs update only what changed. Date-partitioned facts. Birst builds its own semantic layer, so Datrise lands conformed, well-keyed tables it can automate against.
Ideal for networked, governed enterprise BI.
Endpoints
Smaily: Email and SMS campaigns with subscriber segments.
Birst: Cloud BI with networked analytics and enterprise semantic layers.
How Smaily entities map to Birst
| Smaily entity | Birst object | Notes |
|---|---|---|
| subscribers | smaily_subscribers | id PK · custom fields → flattened columns |
| campaigns | smaily_campaigns | id PK · linked to smaily_subscribers |
| lists | smaily_lists | id PK · linked to smaily_subscribers |
| autoresponders | smaily_autoresponders | id PK · linked to smaily_subscribers |
FAQ
How does Datrise handle Smaily's custom fields in Birst?
Flexible values are stored as flattened columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Birst types.
How does the Smaily to Birst sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the source tables Birst ingests.
Related pipelines
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Early access
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