DatriseAI-first ETL

Sailthru to Databricks SQL Warehouse Integration

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

How Datrise loads Sailthru into Databricks SQL Warehouse

Datrise syncs Sailthru's users, campaigns, blasts, message events, lists, and content items 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

Sailthru: Personalized email and onsite content targeting.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Sailthru entities map to Databricks SQL Warehouse

Sailthru entityDatabricks SQL Warehouse objectNotes
userssailthru_usersid PK · custom fields → VARIANT or STRUCT columns
campaignssailthru_campaignsid PK · linked to sailthru_users
blastssailthru_blastsid PK · linked to sailthru_users
message eventssailthru_message_eventsTIMESTAMP events

FAQ

How does Datrise handle Sailthru'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 Sailthru 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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