DatriseAI-first ETL

Harness Amazon DynamoDB

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

How Datrise loads Harness into Amazon DynamoDB

Datrise syncs Harness's records, events, and configuration objects 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

Harness: SaaS or API data source for analytics and warehouse sync.

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

How Harness entities map to Amazon DynamoDB

Harness entityAmazon DynamoDB objectNotes
recordsharness_recordsid PK · custom fields → nested map/list attributes
eventsharness_eventsISO-8601 string or epoch number attributes events
configuration objectsharness_configuration_objectsid PK · linked to harness_records

FAQ

How does Datrise handle Harness'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 Harness 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

Connect Harness to Amazon DynamoDB the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.