DatriseAI-first ETL

Revinate to Databricks SQL Warehouse Integration

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

How Datrise loads Revinate into Databricks SQL Warehouse

Datrise syncs Revinate's guests, reservations, reviews, campaigns, hotels, and guest profiles 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

Revinate: Hospitality guest data and reputation management.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Revinate entities map to Databricks SQL Warehouse

Revinate entityDatabricks SQL Warehouse objectNotes
guestsrevinate_guestsid PK · custom fields → VARIANT or STRUCT columns
reservationsrevinate_reservationsid PK · linked to revinate_guests
reviewsrevinate_reviewsid PK · linked to revinate_guests
campaignsrevinate_campaignsid PK · linked to revinate_guests

FAQ

How does Datrise handle Revinate'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 Revinate 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

Early access

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