DatriseAI-first ETL

Wise Agent to Databricks SQL Warehouse Integration

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

How Datrise loads Wise Agent into Databricks SQL Warehouse

Datrise syncs Wise Agent's contacts, transactions, listings, commissions, referrals, and checklists 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

Wise Agent: Real estate CRM for transactions, commissions, and referrals.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Wise Agent entities map to Databricks SQL Warehouse

Wise Agent entityDatabricks SQL Warehouse objectNotes
contactswise_agent_contactsid PK · custom fields → VARIANT or STRUCT columns
transactionswise_agent_transactionsid PK · linked to wise_agent_contacts
listingswise_agent_listingsid PK · linked to wise_agent_contacts
commissionswise_agent_commissionsid PK · linked to wise_agent_contacts

FAQ

How does Datrise handle Wise Agent'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 Wise Agent 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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