DatriseAI-first ETL

Keap Amazon DynamoDB

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

How Datrise loads Keap into Amazon DynamoDB

Datrise syncs Keap's SMB contacts, opportunities, automations, and appointment workflows 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

Keap: SMB CRM with pipeline automation, email, and appointment flows.

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

How Keap entities map to Amazon DynamoDB

Keap entityAmazon DynamoDB objectNotes
SMB contactskeap_smb_contactsid PK · custom fields → nested map/list attributes
opportunitieskeap_opportunitiesid PK · linked to keap_smb_contacts
automationskeap_automationsid PK · linked to keap_smb_contacts
appointment workflowskeap_appointment_workflowsid PK · linked to keap_smb_contacts

FAQ

How does Datrise handle Keap'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 Keap 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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