DatriseAI-first ETL

Unleash to Sisense Integration

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

How Datrise loads Unleash into Sisense

Datrise syncs Unleash's feature toggles, strategies, environments, projects, metrics, and toggle 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

Unleash: Open-source feature flags and rollout strategies.

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

How Unleash entities map to Sisense

Unleash entitySisense objectNotes
feature togglesunleash_feature_togglesid PK · custom fields → flattened columns for the cube
strategiesunleash_strategiesid PK · linked to unleash_feature_toggles
environmentsunleash_environmentsid PK · linked to unleash_feature_toggles
projectsunleash_projectsid PK · linked to unleash_feature_toggles

FAQ

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

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

Related pipelines

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