DatriseAI-first ETL

Sellsy to Amazon DynamoDB Integration

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

How Datrise loads Sellsy into Amazon DynamoDB

Datrise syncs Sellsy's prospects, opportunities, estimates, invoices, tickets, and timeline events 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

Sellsy: French CRM with quoting, invoicing, and support tickets.

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

How Sellsy entities map to Amazon DynamoDB

Sellsy entityAmazon DynamoDB objectNotes
prospectssellsy_prospectsid PK · custom fields → nested map/list attributes
opportunitiessellsy_opportunitiesid PK · linked to sellsy_prospects
estimatessellsy_estimatesid PK · linked to sellsy_prospects
invoicessellsy_invoicesid PK · linked to sellsy_prospects

FAQ

How does Datrise handle Sellsy'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 Sellsy 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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