Deveoped an Order Management System OMS Prototype for the sporting goods industry

Projects & Collaboration
1

My name is Dieter

I have over 40 years extensive experience on the highest level level of global technologies and represented the instrumental driving force in moving various corporations technology strategy to expand their roles in the ever evolving enterprise market. In the last 20 years I have been directing global sporting goods companies including re-engineering theire IT . Nearly all IT systems I'm aware of use relational databases either SQL or propitiatory code driven.

Why Neo4j?
Neo4j's technology is based on the graph theory offering an impressive ease of use functionality and it says to manage ~34 billion nodes and ~34 billion relationships. Nearly all applications are for my best knowledge information retrieval oriented.
But they also include CRUD (CreateReadUpdateDelete) functionality allowing basically to mange Operational Systems like e.g. complex orders of any company size. This type of technology would drastically reduce the IT workforce and enhance user competencies. Therefore I decided to develop an OMS for the sporting goods industry which is now available as a desk top version and also on the Neo4j-Aura cloud.

OMS Project characteristics:

1. Application description

The prototype “OMS Sporting goods prototype was developed with the graph based database Neo4j including the bloom tool. A full-fletched Order Management System (OMS) with CRUD functionality is now available allowing to manage success critical key areas like:
• Global Style Master: Model (wear type, material,pricing), Product (colors, NRF, Pantone), Item (International sizes)
• Customer Master
• Customer Purchase Orders -CPO's ( Dates, destinations)
• CPO – details ( pricing, quantities, gender..)
• Supplier Master
• Supplier Purchase Order – SPO's (Dates, destinations)
• SPO – details (pricing, quantities
• DC – Inventories (3 DC Locations)
• Employees (Customer and Supplier related)
2. Data
• all from Adidas (copied from the internet; Models: 141, Products: 428, Items: 1,000, Customers: 91, Suppliers:16 )
*Hyper entities: 12
• Entities :36,504
• Relations:58,189
• Label properties: ~400,000
3. Neo4j
• version 5.11-aura cloud version, written in Java, Query language: cypher
4. Hardware:
• Desktop: SHINOBE Tower
• Processor: Intel I5 12 Thread, 4.3 GHz
• RAM: DRAM (DDR 4) 16 GB
• SSD: 256 GB C-Drive
• HDD: 1 TB D-Drive
5. Project
• Author: Dieter Schönegger
• Developer Dieter Schönegger
• Lead-time 1 year
• Resources 1 MJ

1 Like
2

Hi Dieter,

I’d love to hear about your experience using Neo4j for building a Line of Business (LOB) application. As a longtime RDBMS user turned Graph Database enthusiast, I’ve been advocating that Graphs go far beyond traditional Knowledge Graph use cases like fraud detection, recommendations, and IT operations, and most recently Graph RAG for improving GenAI outputs.

While Graphs excel at extracting insights from existing LOB data and also improving GenAI, they’re also powerful for building LOB applications themselves—like your OMS system. By structuring data as a Graph from the start, businesses can seamlessly derive knowledge in real time rather than as an afterthought. And there are many other benefits that Graph bring when building LOB applications.

Looking forward to your perspective and experience in using Graphs!

Best, Marcos