Optimizing Laravel's Eloquent ORM for High-Scale Applications - NextGenBeing Optimizing Laravel's Eloquent ORM for High-Scale Applications - NextGenBeing
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Deep Dive into Laravel's Eloquent ORM: Lessons Learned from Scaling to 10M Requests/Day

Learn how to optimize Laravel's Eloquent ORM for high-scale applications, including eager loading, indexes, and performance testing.

Web Development Premium Content 3 min read
NextGenBeing Founder

NextGenBeing Founder

Jan 2, 2026 7 views
Deep Dive into Laravel's Eloquent ORM: Lessons Learned from Scaling to 10M Requests/Day
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Introduction to Eloquent ORM

I still remember the day our team discovered that our Laravel application's database connection pool was maxed out. We had scaled to 10M requests/day, and our default approach to database interactions was failing us. That's when we dove deep into Laravel's Eloquent ORM, and what we learned changed everything.

The Problem with Default Eloquent Usage

When I first started using Eloquent, I thought it was just a simple ORM that allowed me to interact with my database using PHP objects. But as our application grew, I realized that the default usage patterns were not optimized for high-scale applications. For example, the N+1 query problem was killing our performance.

Solving the N+1 Query Problem

To solve the N+1 query problem, we started using Eloquent's eager loading feature. We loaded related models in a single query, reducing the number of database queries significantly.

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  • Complete step-by-step implementation guide
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  • Real-world examples and metrics

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