DatriseAI-first ETL

ChartMogul to Amazon DynamoDB Integration

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

How Datrise loads ChartMogul into Amazon DynamoDB

Datrise syncs ChartMogul's customers, subscriptions, invoices, MRR movements, plans, and churn 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

ChartMogul: Subscription analytics and revenue reporting.

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

How ChartMogul entities map to Amazon DynamoDB

ChartMogul entityAmazon DynamoDB objectNotes
customerschartmogul_customersid PK · custom fields → nested map/list attributes
subscriptionschartmogul_subscriptionsid PK · linked to chartmogul_customers
invoiceschartmogul_invoicesid PK · linked to chartmogul_customers
MRR movementschartmogul_mrr_movementsISO-8601 string or epoch number attributes events

FAQ

How does Datrise handle ChartMogul'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 ChartMogul 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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