DatriseAI-first ETL

Flexport to Sisense Integration

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

How Datrise loads Flexport into Sisense

Datrise syncs Flexport's shipments, containers, bookings, invoices, milestones, and products 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

Flexport: Freight forwarding and supply chain visibility.

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

How Flexport entities map to Sisense

Flexport entitySisense objectNotes
shipmentsflexport_shipmentsid PK · custom fields → flattened columns for the cube
containersflexport_containersid PK · linked to flexport_shipments
bookingsflexport_bookingsid PK · linked to flexport_shipments
invoicesflexport_invoicesid PK · linked to flexport_shipments

FAQ

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

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

Related pipelines

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