DatriseAI-first ETL

Brevo to Databricks SQL Warehouse Integration

AI-first ETL from Brevo into Databricks SQL Warehouse. Governed entities, incremental sync, typed landing tables.

How Datrise loads Brevo into Databricks SQL Warehouse

Datrise syncs Brevo's contacts, lists, campaigns, transactional emails, deals, and email events into Databricks SQL Warehouse as a Delta Lake table per source entity. Flexible or custom fields land in VARIANT or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.

Sync is incremental: Datrise uses a Delta MERGE on stable id, with change history available via time travel, so re-runs update only what changed. Delta partitioning by load date with OPTIMIZE/Z-ORDER on query keys. Datrise writes Unity Catalog–governed Delta tables, so lineage and permissions are managed centrally rather than per-notebook.

Ideal for lakehouse analytics and ML feature tables on Databricks.

Endpoints

Brevo: Email, SMS, and CRM for small business lifecycle marketing.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Brevo entities map to Databricks SQL Warehouse

Brevo entityDatabricks SQL Warehouse objectNotes
contactsbrevo_contactsid PK · custom fields → VARIANT or STRUCT columns
listsbrevo_listsid PK · linked to brevo_contacts
campaignsbrevo_campaignsid PK · linked to brevo_contacts
transactional emailsbrevo_transactional_emailsid PK · linked to brevo_contacts

FAQ

How does Datrise handle Brevo's custom fields in Databricks SQL Warehouse?

Flexible values are stored as VARIANT or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Databricks SQL Warehouse types.

How does the Brevo to Databricks SQL Warehouse sync stay up to date?

It runs incrementally — Datrise uses a Delta MERGE on stable id, with change history available via time travel.

Related pipelines

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