DatriseAI-first ETL

MoEngage Sisense

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

How Datrise loads MoEngage into Sisense

Datrise syncs MoEngage's engagement events, campaign performance, and retention behavior signals 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

MoEngage: Customer engagement source for campaigns and retention metrics.

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

How MoEngage entities map to Sisense

MoEngage entitySisense objectNotes
engagement eventsmoengage_engagement_eventsdate/time fields events
campaign performancemoengage_campaign_performanceid PK · linked to moengage_engagement_events
retention behavior signalsmoengage_retention_behavior_signalsid PK · linked to moengage_engagement_events

FAQ

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

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

Related pipelines

Early access

Connect MoEngage to Sisense the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.