DatriseAI-first ETL

Manatal to Amazon DynamoDB Integration

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

How Datrise loads Manatal into Amazon DynamoDB

Datrise syncs Manatal's candidates, jobs, applications, pipeline stages, match scores, and clients 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

Manatal: AI recruitment software with candidate scoring.

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

How Manatal entities map to Amazon DynamoDB

Manatal entityAmazon DynamoDB objectNotes
candidatesmanatal_candidatesid PK · custom fields → nested map/list attributes
jobsmanatal_jobsid PK · linked to manatal_candidates
applicationsmanatal_applicationsid PK · linked to manatal_candidates
pipeline stagesmanatal_pipeline_stagesid PK · linked to manatal_candidates

FAQ

How does Datrise handle Manatal'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 Manatal 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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