DatriseAI-first ETL

Close Amazon DynamoDB

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

How Datrise loads Close into Amazon DynamoDB

Datrise syncs Close's leads, opportunities, calls, SMS events, and sequence performance 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

Close: Inside-sales CRM with calling and sequences.

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

How Close entities map to Amazon DynamoDB

Close entityAmazon DynamoDB objectNotes
leadsclose_leadsid PK · custom fields → nested map/list attributes
opportunitiesclose_opportunitiesid PK · linked to close_leads
callsclose_callsid PK · linked to close_leads
SMS eventsclose_sms_eventsISO-8601 string or epoch number attributes events

FAQ

How does Datrise handle Close'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 Close 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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