DatriseAI-first ETL

HubSpot CRM DuckDB

AI-first ETL from HubSpot CRM into DuckDB. Governed entities, incremental sync, typed landing tables.

How Datrise loads HubSpot CRM into DuckDB

Datrise syncs HubSpot CRM's contacts, companies, deals, lifecycle stages, and engagement events into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.

Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.

Ideal for local and notebook analytics without standing up a server.

Endpoints

HubSpot CRM: Inbound CRM with marketing, sales, and service hubs.

DuckDB: In-process analytics database for fast local OLAP.

How HubSpot CRM entities map to DuckDB

HubSpot CRM entityDuckDB objectNotes
contactshubspot_contactsid PK · custom fields → JSON or STRUCT columns
companieshubspot_companiesid PK · linked to hubspot_contacts
dealshubspot_dealsid PK · linked to hubspot_contacts
lifecycle stageshubspot_lifecycle_stagesid PK · linked to hubspot_contacts

FAQ

How does Datrise handle HubSpot CRM's custom fields in DuckDB?

Flexible values are stored as JSON or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native DuckDB types.

How does the HubSpot CRM to DuckDB sync stay up to date?

It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.

Related pipelines

Early access

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