DatriseAI-first ETL

Real Geeks Databricks SQL Warehouse

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

How Datrise loads Real Geeks into Databricks SQL Warehouse

Datrise syncs Real Geeks's contacts, accounts, deals, activities, and lifecycle events 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

Real Geeks: Real estate CRM for leads, listings, and agent follow-up.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Real Geeks entities map to Databricks SQL Warehouse

Real Geeks entityDatabricks SQL Warehouse objectNotes
contactsreal_geeks_contactsid PK · custom fields → VARIANT or STRUCT columns
accountsreal_geeks_accountsid PK · linked to real_geeks_contacts
dealsreal_geeks_dealsid PK · linked to real_geeks_contacts
activitiesreal_geeks_activitiesTIMESTAMP events

FAQ

How does Datrise handle Real Geeks'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 Real Geeks 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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