https://github.com/mariamabidi/order-management-site

A real-time OMS built with Redis, MongoDB, and Python to optimize inventory tracking and order processing. It features real-time updates with Redis Streams, low-stock alerts via Pub/Sub and email, and inventory analytics using Sorted Sets. Persistence is ensured through Redis RDB snapshots and AOF logging.
https://github.com/mariamabidi/order-management-site

nosql-database python3 redis redis-database

Last synced: about 2 months ago
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A real-time OMS built with Redis, MongoDB, and Python to optimize inventory tracking and order processing. It features real-time updates with Redis Streams, low-stock alerts via Pub/Sub and email, and inventory analytics using Sorted Sets. Persistence is ensured through Redis RDB snapshots and AOF logging.

• Host: GitHub
• URL: https://github.com/mariamabidi/order-management-site
• Owner: mariamabidi
• Created: 2024-10-18T21:12:07.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-12-31T09:47:32.000Z (over 1 year ago)
• Last Synced: 2025-08-01T07:06:42.237Z (11 months ago)
• Topics: nosql-database, python3, redis, redis-database
• Language: Python
• Homepage:
• Size: 7.61 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Order-Management-Site

Overview

This project implements a real-time Order Management System (OMS) using Redis, MongoDB, and Python. Designed for efficiency and scalability, the system ensures rapid order processing, dynamic inventory updates, and insightful analytics for modern e-commerce platforms.

Features

 - Real-Time Order Processing: Utilizes Redis Streams to handle continuous incoming orders.

 - Inventory Management: Real-time stock adjustments with Redis Sets and Lists, with low-stock alerts via Pub/Sub.

 - Analytics & Insights: Tracks top-ordered items and inventory trends using Redis Sorted Sets.

 - Alert System: Sends email notifications for low-stock items.

 - Data Persistence: Achieved with Redis RDB snapshots and AOF logging for reliability.

Technologies Used

 - Redis: In-memory database for ultra-fast data operations.

 - MongoDB: Primary data store for order details.

 - Python: Backend logic, including inventory updates and alerting mechanisms.

Contributions

 - Mariam Abidi: Managed Redis Streams, order tracking, and analytics.

 - Suhas Vittal: Handled inventory uploads, stock updates and state management.