DatriseAI-first ETL

Zendesk Amazon DynamoDB

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

How Datrise loads Zendesk into Amazon DynamoDB

Datrise syncs Zendesk's tickets, users, organizations, macros, and satisfaction ratings 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

Zendesk: Customer support suite with tickets and knowledge base.

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

How Zendesk entities map to Amazon DynamoDB

Zendesk entityAmazon DynamoDB objectNotes
ticketszendesk_ticketsid PK · custom fields → nested map/list attributes
userszendesk_usersid PK · linked to zendesk_tickets
organizationszendesk_organizationsid PK · linked to zendesk_tickets
macroszendesk_macrosid PK · linked to zendesk_tickets

FAQ

How does Datrise handle Zendesk'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 Zendesk 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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