HubSpot connector
The managed HubSpot connector in Lakeflow Connect allows you to ingest data from HubSpot Marketing Hub and CRM Hub into Databricks.
Ingestion from HubSpot CRM Hub is in Beta. See Configure OAuth for HubSpot ingestion.
Feature availability
Feature | Availability |
|---|---|
UI-based pipeline authoring |
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API-based pipeline authoring |
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Declarative Automation Bundles |
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Incremental ingestion |
Some tables support incremental ingestion. Other tables require a full refresh. See HubSpot connector reference. |
Unity Catalog governance |
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Orchestration using Databricks Workflows |
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SCD type 2 |
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API-based column selection and deselection |
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API-based row filtering |
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Automated schema evolution: New and deleted columns |
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Automated schema evolution: Data type changes |
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Automated schema evolution: Column renames |
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Automated schema evolution: New tables |
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Maximum number of tables per pipeline | 250 |
Authentication methods
Authentication method | Availability |
|---|---|
OAuth U2M |
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OAuth M2M |
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OAuth (manual refresh token) |
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Basic authentication (username/password) |
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Basic authentication (API key) |
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Basic authentication (service account JSON key) |
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What to know before you start
Topic | Why it matters |
|---|---|
The workflow depends on your Databricks user persona:
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The steps to create a connection depend on the authentication method you choose. | |
The steps to create a pipeline depend on the interface. | |
The pipeline schedule depends on your latency and cost requirements. | |
Depending on your ingestion needs, the pipeline might use configurations like history tracking, column selection, and row filtering. Supported configurations vary by connector. See Feature availability. |
Start ingesting from HubSpot
The following table provides an overview of the end-to-end HubSpot ingestion flow, based on user type:
User | Steps |
|---|---|
Admin |
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Non-admin | Use any supported interface to create a pipeline from an existing connection. See Ingest data from HubSpot. |