Salesforce Marketing Cloud to DuckDB Integration

How Datrise loads Salesforce Marketing Cloud into DuckDB

Datrise syncs Salesforce Marketing Cloud's subscribers, data extensions, journeys, sends, email events, and lists 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 Marketing Cloud: Enterprise email, journeys, and cross-channel messaging.

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

How Salesforce Marketing Cloud entities map to DuckDB

Salesforce Marketing Cloud entity	DuckDB object	Notes
subscribers	`salesforce_marketing_cloud_subscribers`	id PK · custom fields → JSON or STRUCT columns
data extensions	`salesforce_marketing_cloud_data_extensions`	id PK · linked to salesforce_marketing_cloud_subscribers
journeys	`salesforce_marketing_cloud_journeys`	id PK · linked to salesforce_marketing_cloud_subscribers
sends	`salesforce_marketing_cloud_sends`	id PK · linked to salesforce_marketing_cloud_subscribers

FAQ

How does Datrise handle Salesforce Marketing 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 Marketing 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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