DatriseAI-first ETL

Selligent to Databricks SQL Warehouse Integration

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

How Datrise loads Selligent into Databricks SQL Warehouse

Datrise syncs Selligent's contacts, journeys, campaigns, message events, lists, and real-time triggers 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

Selligent: Enterprise cross-channel campaigns with real-time triggers.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Selligent entities map to Databricks SQL Warehouse

Selligent entityDatabricks SQL Warehouse objectNotes
contactsselligent_contactsid PK · custom fields → VARIANT or STRUCT columns
journeysselligent_journeysid PK · linked to selligent_contacts
campaignsselligent_campaignsid PK · linked to selligent_contacts
message eventsselligent_message_eventsTIMESTAMP events

FAQ

How does Datrise handle Selligent'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 Selligent 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.

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Early access

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