DatriseAI-first ETL

Flexport to Snowflake Integration

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

How Datrise loads Flexport into Snowflake

Datrise syncs Flexport's shipments, containers, bookings, invoices, milestones, and products into Snowflake as a typed table per source entity. Flexible or custom fields land in VARIANT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP_TZ.

Sync is incremental: Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size, so re-runs update only what changed. Automatic micro-partitioning, with optional clustering keys on high-cardinality ids. Snowflake upper-cases unquoted identifiers, so Datrise standardizes on lower-case quoted names to keep column references stable.

Ideal for central analytics warehouses feeding BI and AI workloads.

Endpoints

Flexport: Freight forwarding and supply chain visibility.

Snowflake: Cloud data warehouse with separated compute and storage.

How Flexport entities map to Snowflake

Flexport entitySnowflake objectNotes
shipmentsflexport_shipmentsid PK · custom fields → VARIANT columns
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 Snowflake?

Flexible values are stored as VARIANT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Snowflake types.

How does the Flexport to Snowflake sync stay up to date?

It runs incrementally — Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size.

Related pipelines

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