https://chatgpt.com/share/67ac73d0-8128-8012-a3d7-b4ef3c5f4bb4

Below is an extended, beginner-friendly version of the development guide. Each section now includes real-world examples, sample SQL commands, and clear explanations to help your team at nin.in/trade understand and implement these techniques step by step.

1. Overview & Objectives

Goal:

We want our trading platform to handle large amounts of data efficiently while remaining easy to maintain. Our focus is on:

• Optimizing performance: Tuning PostgreSQL settings, using partitions, and caching query results.
• Simplifying complex queries: Denormalizing data and using materialized views.
• Building a resilient system: Through proper backup, monitoring, and automation.

2. Data Modeling & Schema Design

Denormalization & Materialized Views

What It Means:

Instead of having many related tables (which require JOINs), we sometimes store related data together. This can speed up queries because the database doesn’t have to search through several tables.

Example – Denormalized Table:

Suppose you have two tables:

• users: Contains user details (id, name, email)
• orders: Contains order details (order_id, user_id, product, price)

A normalized design might require a JOIN: