DatriseAI-first ETL

Branch to Databricks SQL Warehouse Integration

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

How Datrise loads Branch into Databricks SQL Warehouse

Datrise syncs Branch's links, clicks, installs, events, attribution touchpoints, and 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

Branch: Deep linking and mobile attribution.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Branch entities map to Databricks SQL Warehouse

Branch entityDatabricks SQL Warehouse objectNotes
linksbranch_linksid PK · custom fields → VARIANT or STRUCT columns
clicksbranch_clicksid PK · linked to branch_links
installsbranch_installsid PK · linked to branch_links
eventsbranch_eventsTIMESTAMP events

FAQ

How does Datrise handle Branch'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 Branch 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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