DatriseAI-first ETL

Attio Amazon DynamoDB

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

How Datrise loads Attio into Amazon DynamoDB

Datrise syncs Attio's objects, lists, records, notes, and relationship 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

Attio: Modern CRM source for relationship and pipeline data.

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

How Attio entities map to Amazon DynamoDB

Attio entityAmazon DynamoDB objectNotes
objectsattio_objectsid PK · custom fields → nested map/list attributes
listsattio_listsid PK · linked to attio_objects
recordsattio_recordsid PK · linked to attio_objects
notesattio_notesid PK · linked to attio_objects

FAQ

How does Datrise handle Attio'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 Attio 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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