DatriseAI-first ETL

Lofty to Amazon DynamoDB Integration

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

How Datrise loads Lofty into Amazon DynamoDB

Datrise syncs Lofty's leads, contacts, listings, property searches, smart plans, and tour requests 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

Lofty: Real estate CRM with IDX search and AI lead nurture.

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

How Lofty entities map to Amazon DynamoDB

Lofty entityAmazon DynamoDB objectNotes
leadslofty_leadsid PK · custom fields → nested map/list attributes
contactslofty_contactsid PK · linked to lofty_leads
listingslofty_listingsid PK · linked to lofty_leads
property searcheslofty_property_searchesid PK · linked to lofty_leads

FAQ

How does Datrise handle Lofty'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 Lofty 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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