DatriseAI-first ETL

Sendwithus to Sisense Integration

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

How Datrise loads Sendwithus into Sisense

Datrise syncs Sendwithus's templates, sends, customers, delivery events, versions, and drip campaigns 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

Sendwithus: Templated transactional email and A/B testing.

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

How Sendwithus entities map to Sisense

Sendwithus entitySisense objectNotes
templatessendwithus_templatesid PK · custom fields → flattened columns for the cube
sendssendwithus_sendsid PK · linked to sendwithus_templates
customerssendwithus_customersid PK · linked to sendwithus_templates
delivery eventssendwithus_delivery_eventsdate/time fields events

FAQ

How does Datrise handle Sendwithus'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 Sendwithus to Sisense sync stay up to date?

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

Related pipelines

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