DatriseAI-first ETL

Amplitude Sisense

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

How Datrise loads Amplitude into Sisense

Datrise syncs Amplitude's product events, user properties, funnels, cohorts, and retention curves 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

Amplitude: Product analytics source for events, funnels, and cohorts.

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

How Amplitude entities map to Sisense

Amplitude entitySisense objectNotes
product eventsamplitude_product_eventsdate/time fields events
user propertiesamplitude_user_propertiesid PK · linked to amplitude_product_events
funnelsamplitude_funnelsid PK · linked to amplitude_product_events
cohortsamplitude_cohortsid PK · linked to amplitude_product_events

FAQ

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

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

Related pipelines

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