Klaviyo → Birst
AI-first ETL from Klaviyo into Birst. Governed entities, incremental sync, typed landing tables.
How Datrise loads Klaviyo into Birst
Datrise syncs Klaviyo's profiles, segments, flows, campaigns, and attributed revenue 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
Klaviyo: E-commerce marketing automation with email and SMS.
Birst: Cloud BI with networked analytics and enterprise semantic layers.
How Klaviyo entities map to Birst
| Klaviyo entity | Birst object | Notes |
|---|---|---|
| profiles | klaviyo_profiles | id PK · custom fields → flattened columns |
| segments | klaviyo_segments | id PK · linked to klaviyo_profiles |
| flows | klaviyo_flows | id PK · linked to klaviyo_profiles |
| campaigns | klaviyo_campaigns | id PK · linked to klaviyo_profiles |
FAQ
How does Datrise handle Klaviyo'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 Klaviyo to Birst sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the source tables Birst ingests.
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Early access
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