ForceManager to DuckDB Integration

How Datrise loads ForceManager into DuckDB

Datrise syncs ForceManager's accounts, contacts, opportunities, visits, activities, and sales routes 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

ForceManager: Mobile-first CRM for field sales reps and visit tracking.

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

How ForceManager entities map to DuckDB

ForceManager entity	DuckDB object	Notes
accounts	`forcemanager_accounts`	id PK · custom fields → JSON or STRUCT columns
contacts	`forcemanager_contacts`	id PK · linked to forcemanager_accounts
opportunities	`forcemanager_opportunities`	id PK · linked to forcemanager_accounts
visits	`forcemanager_visits`	id PK · linked to forcemanager_accounts

FAQ

How does Datrise handle ForceManager'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 ForceManager 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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