Discover 41 articles on Caching in mobile performance
Showing 20 of 41 articles (Page 1 of 3)
Essam Fahmy from Deloitte reveals why 70% of users abandon slow apps—and shares the exact techniques that cut load times by up to 70%. If your mobile team treats performance as an afterthought, this breakdown w...
Todoist's iOS app became nearly unusable for some users after migrating from Realm to GRDB. The culprit? A SQL query generating 128,136 intermediate rows from just 399 actual records.
Your Flutter app is making the same API calls over and over. Every screen load, every refresh—wasting bandwidth, draining batteries, and frustrating users with unnecessary wait times.
Shopify had 600 mobile screens to build. Building them all natively would have crushed their velocity, but WebViews felt slow and broken.
Ankit Bhalla from Cars24 tackles the double-edged sword of mobile caching: it can make your React Native app blazing fast or turn it into a buggy nightmare. Here's how to get it right.
Shopify's mobile app was getting slower after migrating to React Native. So they spent a year making it blazingly fast again.
CRED Engineering faced a nightmare: caching every query combination would require 45,768+ TB of storage. Here's how they got it down to 135 MB.
Swiggy's mobile apps serve millions of users across wildly different devices and network conditions. How do you deliver high-quality images and videos without killing performance or burning through bandwidth co...
Slack's mobile team faces a unique challenge: users expect desktop-level performance while bouncing between subway tunnels and spotty cellular networks.
Pepperfry's engineering team was facing system hangs and 28% CPU usage just from scrolling. The culprit? Traditional scroll event listeners that were choking their main thread.
Swiggy was bleeding money on video bandwidth costs. The culprit? Videos being requested at 270px, 272px, 275px... you get the idea.
Instagram's disk cache was causing more crashes than any other component in their Android app. The culprit? A well-intentioned open source library that made error handling a developer nightmare.
Swiggy's mobile team faced a common problem: juggling disk caches, LRU caches, and databases without creating a maintenance nightmare. Here's their elegant solution.
Swiggy's iOS team built Instagram-style video stories and saved 49GB of user data in just two weeks. Here's how they did it.
Delivery Hero was burning through 9TB of image data daily. Their apps were sluggish, their network costs were astronomical, and users were waiting too long for images to load.
Pinterest's API team just freed up 4.5GB of memory per host with a clever database swap. The result? Fewer servers, happier users, and a masterclass in optimization.
Klarna's team removed their caching layer and saw a 25% performance boost. Wait, what?
LazyPay was serving unoptimized images directly from S3, killing app performance and burning bandwidth. Their migration to Cloudinary cut image sizes by 70%.
DoorDash makes millions of ML predictions per second, but their Redis-based feature store was becoming a massive cost and scalability bottleneck. Could client-side caching be the answer?
Spotify just open-sourced the tool that slashed their iOS build times by 70%. For teams drowning in long compile times, this is a game-changer.