DatriseAI-first ETL

Day.ai Amazon DynamoDB

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

How Datrise loads Day.ai into Amazon DynamoDB

Datrise syncs Day.ai's contacts, accounts, deals, activities, and lifecycle 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

Day.ai: AI-native CRM for relationship data, enrichment, and workflow automation.

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

How Day.ai entities map to Amazon DynamoDB

Day.ai entityAmazon DynamoDB objectNotes
contactsday_ai_contactsid PK · custom fields → nested map/list attributes
accountsday_ai_accountsid PK · linked to day_ai_contacts
dealsday_ai_dealsid PK · linked to day_ai_contacts
activitiesday_ai_activitiesISO-8601 string or epoch number attributes events

FAQ

How does Datrise handle Day.ai'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 Day.ai 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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