DatriseAI-first ETL

Veeva CRM to Amazon DynamoDB Integration

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

How Datrise loads Veeva CRM into Amazon DynamoDB

Datrise syncs Veeva CRM's accounts, calls, samples, territories, consents, and medical inquiries 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

Veeva CRM: Life sciences CRM for field medical and commercial teams.

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

How Veeva CRM entities map to Amazon DynamoDB

Veeva CRM entityAmazon DynamoDB objectNotes
accountsveeva_accountsid PK · custom fields → nested map/list attributes
callsveeva_callsid PK · linked to veeva_accounts
samplesveeva_samplesid PK · linked to veeva_accounts
territoriesveeva_territoriesid PK · linked to veeva_accounts

FAQ

How does Datrise handle Veeva CRM'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 Veeva CRM 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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