DatriseAI-first ETL

ForceManager to Amazon DynamoDB Integration

AI-first ETL from ForceManager into Amazon DynamoDB. Governed entities, incremental sync, typed landing tables.

How Datrise loads ForceManager into Amazon DynamoDB

Datrise syncs ForceManager's accounts, contacts, opportunities, visits, activities, and sales routes into Amazon DynamoDB as an item per source record in a table per entity. Flexible or custom fields land in nested map/list attributes, and timestamps such as created, updated, and status changes are typed as ISO-8601 string or epoch number attributes.

Sync is incremental: Datrise uses PutItem/UpdateItem keyed on a partition key derived from the entity id, so re-runs update only what changed. Partition-key design on the entity id to spread throughput evenly. DynamoDB rewards access-pattern-first key design, so Datrise sets partition/sort keys from your entity ids rather than scan-heavy defaults.

Ideal for serverless apps needing single-digit-millisecond key lookups on CRM data.

Endpoints

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

Amazon DynamoDB: Serverless key-value and document store on AWS.

How ForceManager entities map to Amazon DynamoDB

ForceManager entityAmazon DynamoDB objectNotes
accountsforcemanager_accountsid PK · custom fields → nested map/list attributes
contactsforcemanager_contactsid PK · linked to forcemanager_accounts
opportunitiesforcemanager_opportunitiesid PK · linked to forcemanager_accounts
visitsforcemanager_visitsid PK · linked to forcemanager_accounts

FAQ

How does Datrise handle ForceManager's custom fields in Amazon DynamoDB?

Flexible values are stored as nested map/list attributes, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon DynamoDB types.

How does the ForceManager to Amazon DynamoDB sync stay up to date?

It runs incrementally — Datrise uses PutItem/UpdateItem keyed on a partition key derived from the entity id.

Related pipelines

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