DatriseAI-first ETL

Agendor to Databricks SQL Warehouse Integration

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

How Datrise loads Agendor into Databricks SQL Warehouse

Datrise syncs Agendor's organizations, people, deals, funnel stages, activities, and proposals 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

Agendor: Brazilian sales CRM for pipeline and account follow-up.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Agendor entities map to Databricks SQL Warehouse

Agendor entityDatabricks SQL Warehouse objectNotes
organizationsagendor_organizationsid PK · custom fields → VARIANT or STRUCT columns
peopleagendor_peopleid PK · linked to agendor_organizations
dealsagendor_dealsid PK · linked to agendor_organizations
funnel stagesagendor_funnel_stagesid PK · linked to agendor_organizations

FAQ

How does Datrise handle Agendor'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 Agendor 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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