DatriseAI-first ETL

Customer.io Amazon DynamoDB

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

How Datrise loads Customer.io into Amazon DynamoDB

Datrise syncs Customer.io's profiles, segments, campaigns, deliveries, and conversion events 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

Customer.io: Messaging automation based on product and behavioral data.

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

How Customer.io entities map to Amazon DynamoDB

Customer.io entityAmazon DynamoDB objectNotes
profilescustomer_io_profilesid PK · custom fields → nested map/list attributes
segmentscustomer_io_segmentsid PK · linked to customer_io_profiles
campaignscustomer_io_campaignsid PK · linked to customer_io_profiles
deliveriescustomer_io_deliveriesid PK · linked to customer_io_profiles

FAQ

How does Datrise handle Customer.io'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 Customer.io 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

Early access

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