DatriseAI-first ETL

Listrak to Amazon DynamoDB Integration

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

How Datrise loads Listrak into Amazon DynamoDB

Datrise syncs Listrak's contacts, lists, campaigns, message events, orders, and segments 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

Listrak: Retail email, SMS, and behavioral marketing.

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

How Listrak entities map to Amazon DynamoDB

Listrak entityAmazon DynamoDB objectNotes
contactslistrak_contactsid PK · custom fields → nested map/list attributes
listslistrak_listsid PK · linked to listrak_contacts
campaignslistrak_campaignsid PK · linked to listrak_contacts
message eventslistrak_message_eventsISO-8601 string or epoch number attributes events

FAQ

How does Datrise handle Listrak'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 Listrak 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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