DatriseAI-first ETL

kvCORE Amazon DynamoDB

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

How Datrise loads kvCORE into Amazon DynamoDB

Datrise syncs kvCORE's contacts, accounts, deals, activities, and lifecycle 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

kvCORE: Real estate CRM for leads, listings, and agent follow-up.

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

How kvCORE entities map to Amazon DynamoDB

kvCORE entityAmazon DynamoDB objectNotes
contactskvcore_contactsid PK · custom fields → nested map/list attributes
accountskvcore_accountsid PK · linked to kvcore_contacts
dealskvcore_dealsid PK · linked to kvcore_contacts
activitieskvcore_activitiesISO-8601 string or epoch number attributes events

FAQ

How does Datrise handle kvCORE'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 kvCORE 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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