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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.

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mariamabidi/Order-Management-Site

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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.

About

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.

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