DatriseAI-first ETL

Propertybase Sisense

AI-first ETL from Propertybase into Sisense. Governed entities, incremental sync, typed landing tables.

How Datrise loads Propertybase into Sisense

Datrise syncs Propertybase's contacts, accounts, deals, activities, and lifecycle events into Sisense as modeled tables for a Sisense ElastiCube (or live connection). Flexible or custom fields land in flattened columns for the cube, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental ElastiCube builds on changed rows, so re-runs update only what changed. Date-partitioned facts to speed cube builds. ElastiCube is an in-memory model, so Datrise lands incremental, build-friendly tables rather than forcing full rebuilds.

Ideal for embedded analytics on an in-memory engine.

Endpoints

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

Sisense: Analytics platform with elastic data models and embedded analytics.

How Propertybase entities map to Sisense

Propertybase entitySisense objectNotes
contactspropertybase_contactsid PK · custom fields → flattened columns for the cube
accountspropertybase_accountsid PK · linked to propertybase_contacts
dealspropertybase_dealsid PK · linked to propertybase_contacts
activitiespropertybase_activitiesdate/time fields events

FAQ

How does Datrise handle Propertybase's custom fields in Sisense?

Flexible values are stored as flattened columns for the cube, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Sisense types.

How does the Propertybase to Sisense sync stay up to date?

It runs incrementally — Datrise uses incremental ElastiCube builds on changed rows.

Related pipelines

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