3PL Central to Mode Integration
AI-first ETL from 3PL Central into Mode. Governed entities, incremental sync, typed landing tables.
How Datrise loads 3PL Central into Mode
Datrise syncs 3PL Central's orders, receipts, inventory levels, items, customers, and warehouses into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.
Ideal for SQL-first analysis with Python and R notebooks.
Endpoints
3PL Central: Third-party logistics warehouse and order operations.
Mode: Collaborative analytics workspace for SQL, Python, and shared reports.
How 3PL Central entities map to Mode
| 3PL Central entity | Mode object | Notes |
|---|---|---|
| orders | tplcentral_orders | id PK · custom fields → flattened columns for SQL and notebooks |
| receipts | tplcentral_receipts | id PK · linked to tplcentral_orders |
| inventory levels | tplcentral_inventory_levels | id PK · linked to tplcentral_orders |
| items | tplcentral_items | id PK · linked to tplcentral_orders |
FAQ
How does Datrise handle 3PL Central's custom fields in Mode?
Flexible values are stored as flattened columns for SQL and notebooks, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Mode types.
How does the 3PL Central to Mode sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the queried tables.
Related pipelines
More destinations for 3PL Central
Early access
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