DatriseAI-first ETL

HubSpot Service Hub Databricks SQL Warehouse

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

How Datrise loads HubSpot Service Hub into Databricks SQL Warehouse

Datrise syncs HubSpot Service Hub'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

HubSpot Service Hub: Customer service platform with ticket and conversation context.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How HubSpot Service Hub entities map to Databricks SQL Warehouse

HubSpot Service Hub entityDatabricks SQL Warehouse objectNotes
contactshubspot_service_contactsid PK · custom fields → VARIANT or STRUCT columns
accountshubspot_service_accountsid PK · linked to hubspot_service_contacts
dealshubspot_service_dealsid PK · linked to hubspot_service_contacts
activitieshubspot_service_activitiesTIMESTAMP events

FAQ

How does Datrise handle HubSpot Service Hub'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 HubSpot Service Hub 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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