Salesforce Health Cloud to DuckDB Integration

How Datrise loads Salesforce Health Cloud into DuckDB

Datrise syncs Salesforce Health Cloud's patients, care plans, care teams, clinical encounters, cases, and consents 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

Salesforce Health Cloud: Patient and member relationship management on Salesforce.

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

How Salesforce Health Cloud entities map to DuckDB

Salesforce Health Cloud entity	DuckDB object	Notes
patients	`salesforce_health_cloud_patients`	id PK · custom fields → JSON or STRUCT columns
care plans	`salesforce_health_cloud_care_plans`	id PK · linked to salesforce_health_cloud_patients
care teams	`salesforce_health_cloud_care_teams`	id PK · linked to salesforce_health_cloud_patients
clinical encounters	`salesforce_health_cloud_clinical_encounters`	id PK · linked to salesforce_health_cloud_patients

FAQ

How does Datrise handle Salesforce Health Cloud'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 Salesforce Health Cloud 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

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