DatriseAI-first ETL

Sendwithus to Databricks SQL Warehouse Integration

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

How Datrise loads Sendwithus into Databricks SQL Warehouse

Datrise syncs Sendwithus's templates, sends, customers, delivery events, versions, and drip campaigns 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

Sendwithus: Templated transactional email and A/B testing.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Sendwithus entities map to Databricks SQL Warehouse

Sendwithus entityDatabricks SQL Warehouse objectNotes
templatessendwithus_templatesid PK · custom fields → VARIANT or STRUCT columns
sendssendwithus_sendsid PK · linked to sendwithus_templates
customerssendwithus_customersid PK · linked to sendwithus_templates
delivery eventssendwithus_delivery_eventsTIMESTAMP events

FAQ

How does Datrise handle Sendwithus'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 Sendwithus 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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