DatriseAI-first ETL

Nimble Amazon DynamoDB

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

How Datrise loads Nimble into Amazon DynamoDB

Datrise syncs Nimble's relationship records, deals, tasks, and activity intelligence 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

Nimble: Relationship-focused CRM for SMB sales teams.

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

How Nimble entities map to Amazon DynamoDB

Nimble entityAmazon DynamoDB objectNotes
relationship recordsnimble_relationship_recordsid PK · custom fields → nested map/list attributes
dealsnimble_dealsid PK · linked to nimble_relationship_records
tasksnimble_tasksid PK · linked to nimble_relationship_records
activity intelligencenimble_activity_intelligenceISO-8601 string or epoch number attributes events

FAQ

How does Datrise handle Nimble'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 Nimble 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

Early access

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