Feature Marketplace · Connectors
Oracle NetSuite Connector
Oracle NetSuite cloud ERP. Syncs customers, sales orders, invoices, and inventory items via the SuiteTalk REST Record API (record/v1) with incremental polling on lastModifiedDate.
What syncs
The Oracle NetSuite records STRAX brings into your hub.
Each kind of record is mapped once to your company model in the STRAX hub, then kept current in every system that needs it.
Customers
Customer master records including company name, contact details, balances, and credit terms.
Sales Orders
Sales order transactions including status, totals, currency, and ship dates.
Invoices
Customer invoices including amounts paid and remaining, due dates, and totals.
Inventory Items
Inventory item master records including cost, quantities on hand and available.
Oracle NetSuite data in your own SQL Server, then wherever it is needed.
STRAX is a self-hosted integration platform. The Oracle NetSuite records land in the STRAX hub, a SQL Server database on your own servers, where your reports, portals and workflows read them. From there the hub delivers them to the other systems you connect, whether those run on SQL Server, MySQL, PostgreSQL or another API. STRAX signs in to Oracle NetSuite with an access token that you provide, stored encrypted.
How STRAX connectors work → How the STRAX integration engine works → Connecting a system, in the documentation →
About this listing
| Version | 1.0.1 |
| Author | STRAX |
| Category | Connectors |
| Published | 2026-07-15 |
What's inside
| Connector profile | 1 |
Free listing
Install it from Feature Marketplace inside STRAX
Open Feature Marketplace
In your STRAX installation, open Feature Marketplace from the navigation.
Find "Oracle NetSuite Connector"
Search or browse to this listing and review the contents disclosure; every package shows what it contains before anything runs.
Install
Choose Install, or "Customise with AI" to adapt the package to your environment first. No licence is needed for free listings.
See it on your own systems.
A demo takes an hour, on your data landscape rather than ours.