DatriseAI-first ETL

Recharge Sisense

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

How Datrise loads Recharge into Sisense

Datrise syncs Recharge's subscriptions, charges, customers, plans, and churn 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

Recharge: Subscription commerce for Shopify and recurring billing.

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

How Recharge entities map to Sisense

Recharge entitySisense objectNotes
subscriptionsrecharge_subscriptionsid PK · custom fields → flattened columns for the cube
chargesrecharge_chargesid PK · linked to recharge_subscriptions
customersrecharge_customersid PK · linked to recharge_subscriptions
plansrecharge_plansid PK · linked to recharge_subscriptions

FAQ

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

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

Related pipelines

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