DatriseAI-first ETL

Keap Microsoft SQL Server

AI-first ETL from Keap into Microsoft SQL Server. Governed entities, incremental sync, typed landing tables.

How Datrise loads Keap into Microsoft SQL Server

Datrise syncs Keap's SMB contacts, opportunities, automations, and appointment workflows into Microsoft SQL Server as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.

Sync is incremental: Datrise uses a watermark on updated-at, applied with a MERGE statement, so re-runs update only what changed. Optional partitioned tables on a date partition function. SQL Server defaults to a case-insensitive collation, so Datrise preserves original casing in a metadata column to avoid silent key collisions.

Ideal for Microsoft-stack analytics and Power BI Import models.

Endpoints

Keap: SMB CRM with pipeline automation, email, and appointment flows.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Keap entities map to Microsoft SQL Server

Keap entityMicrosoft SQL Server objectNotes
SMB contactskeap_smb_contactsid PK · custom fields → NVARCHAR(MAX) JSON columns
opportunitieskeap_opportunitiesid PK · linked to keap_smb_contacts
automationskeap_automationsid PK · linked to keap_smb_contacts
appointment workflowskeap_appointment_workflowsid PK · linked to keap_smb_contacts

FAQ

How does Datrise handle Keap's custom fields in Microsoft SQL Server?

Flexible values are stored as NVARCHAR(MAX) JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Microsoft SQL Server types.

How does the Keap to Microsoft SQL Server sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with a MERGE statement.

Related pipelines

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