---
title: "Making Shopify’s Flagship App 20% Faster in 6 Weeks Using a Novel Caching Solution"
description: "Shop’s home feed, the app’s most used feature, aggregated orders from millions of Shopify and non-Shopify merchants plus tracking data from dozens of carriers, accounted for 30% of database load and affected application performance. Before each database update, the custom write-through cache marks a user’s cache invalid, applies the write, then refreshes and revalidates it. To handle concurrent updates, it uses a separate pending-writes key and a short-expiry key to distinguish active writes from interrupted processes, while Active Record Concerns preserve the existing ORM interface. After a staged validation rollout, the cache reduced database load by 15%, overall app latency by about 20%, and overall GraphQL latency by 20%, with a double-digit decrease in CPU usage."
---

# Making Shopify’s Flagship App 20% Faster in 6 Weeks Using a Novel Caching Solution

[Shopify](https://yomu.fyi/company/shopify) · 2023-10-18 · Sep 22, 2021

**Type:** Problem & solution

## Summary

Shop’s home feed, the app’s most used feature, aggregated orders from millions of Shopify and non-Shopify merchants plus tracking data from dozens of carriers, accounted for 30% of database load and affected application performance. Before each database update, the custom write-through cache marks a user’s cache invalid, applies the write, then refreshes and revalidates it. To handle concurrent updates, it uses a separate pending-writes key and a short-expiry key to distinguish active writes from interrupted processes, while Active Record Concerns preserve the existing ORM interface. After a staged validation rollout, the cache reduced database load by 15%, overall app latency by about 20%, and overall GraphQL latency by 20%, with a double-digit decrease in CPU usage.

## Context

Shop’s home feed was the app’s most heavily used feature, but aggregating orders and tracking data was computationally expensive and slow. The feed accounted for 30% of database load, affecting performance across the application. Database-level optimization options were limited, and a large code rewrite was not feasible.

## Approach / What changed

A custom write-through cache was built with distributed Memcached. Before database writes, the user’s cache is marked invalid; after a successful write, it is updated and marked valid. A pending-writes key supports concurrent updates, while a short-expiry key helps identify interrupted processes. Active Record Concerns integrated the behavior without changing the ORM API, and staged testing compared cached and database results before global rollout.

## Takeaways

- The home feed cache uses invalidation before writes and revalidation afterward, preventing cached data from being served while the cache and database are out of sync.
- A per-user pending-writes counter handles concurrent order updates, while a short-expiry key helps distinguish an active write from a process that failed before decrementing the counter.
- After global rollout, database load fell 15%, overall app latency fell about 20%, overall GraphQL latency fell 20%, and CPU usage decreased by double digits.

**Tags:** [Architecture](https://yomu.fyi/topic/architecture), [Caching](https://yomu.fyi/topic/caching), [GraphQL](https://yomu.fyi/topic/graphql), [Performance](https://yomu.fyi/topic/performance), [Scalability](https://yomu.fyi/topic/scalability)

- Source: [Shopify](https://shopify.engineering/shop-app-custom-caching-solution)
- Source URL: https://shopify.engineering/shop-app-custom-caching-solution
- Ingested by Yomu: 2026-08-30T15:29:14.869Z

[Read original post](https://shopify.engineering/shop-app-custom-caching-solution)