DatriseAI-first ETL

HubSpot Operations Hub Mode

AI-first ETL from HubSpot Operations Hub into Mode. Governed entities, incremental sync, typed landing tables.

How Datrise loads HubSpot Operations Hub into Mode

Datrise syncs HubSpot Operations Hub's contacts, accounts, deals, activities, and lifecycle events into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.

Ideal for SQL-first analysis with Python and R notebooks.

Endpoints

HubSpot Operations Hub: CRM for SMB teams managing pipeline, contacts, and customer activity.

Mode: Collaborative analytics workspace for SQL, Python, and shared reports.

How HubSpot Operations Hub entities map to Mode

HubSpot Operations Hub entityMode objectNotes
contactshubspot_operations_contactsid PK · custom fields → flattened columns for SQL and notebooks
accountshubspot_operations_accountsid PK · linked to hubspot_operations_contacts
dealshubspot_operations_dealsid PK · linked to hubspot_operations_contacts
activitieshubspot_operations_activitiestemporal columns events

FAQ

How does Datrise handle HubSpot Operations Hub's custom fields in Mode?

Flexible values are stored as flattened columns for SQL and notebooks, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Mode types.

How does the HubSpot Operations Hub to Mode sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the queried tables.

Related pipelines

Early access

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