DatriseAI-first ETL

Workable to Amazon DynamoDB Integration

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

How Datrise loads Workable into Amazon DynamoDB

Datrise syncs Workable's candidates, jobs, applications, interviews, offers, and pipeline stages 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

Workable: Recruiting pipeline and candidate evaluation.

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

How Workable entities map to Amazon DynamoDB

Workable entityAmazon DynamoDB objectNotes
candidatesworkable_candidatesid PK · custom fields → nested map/list attributes
jobsworkable_jobsid PK · linked to workable_candidates
applicationsworkable_applicationsid PK · linked to workable_candidates
interviewsworkable_interviewsid PK · linked to workable_candidates

FAQ

How does Datrise handle Workable'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 Workable 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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