HHow They ScaledOct 19 · 5 min readHow Figma, Notion and Slack handled shardingHorizontal sharding is the move every team hopes to put off. You take one database, split its rows across many, and suddenly every query, migration and on-call runbook has to know where the data liveshowtheyscaled.hashnode.dev
DDevang PandyaOct 18 · 10 min readVertical vs Horizontal Scaling: How Instagram Scaled With a Tiny TeamBy Devang Pandya · Cloud Tech by Devang · Cloud • DevOps • AI — Made Simple In April 2012, Facebook agreed to buy Instagram for about $1 billion. At that time Instagram had around 30 million users andcloudtechbydevang.hashnode.dev
DDevesh ParmarOct 3 · 7 min readDatabase Sharding: What Happens When One Database Isn't Enough?Imagine you're the engineer at Notion. I have no idea how their stack actually looks inside, so treat this as a thought experiment. Your product has hundreds of millions of users, and everything livesbackend-bytes.hashnode.dev
SSarmeet SinghSep 28 · 57 min readDivide and Conquer: Sharding and Partitioning, Explained Like You're NewIn the URL shortener post, Step 7 had a quiet moment of hand-waving. Billions of URL mappings needed a home, a single database couldn't hold them, and I wrote something like "so we shard it" and movedblueprintsofscale.hashnode.dev
LLakshay DhoundiyalSep 12 · 10 min readThe Hidden Distributed System Behind YouTube’s “Continue Watching” Button 🎬⚙️Imagine this. You’re watching a YouTube video about system design. The explanation is getting interesting. The speaker has just started discussing database sharding. You pause the video at 08:37. Life2lakshaydhoundiyal.hashnode.dev
SSubroto SharmaAug 25 · 5 min readHow to Scale a Database Under Massive User Load: Replication vs ShardingAs an application grows, the database can eventually start struggling with massive user traffic. At that point, one important architectural decision is: Should we use database replication or sharding?subrotosharma.hashnode.dev
MMayank JainJul 11 · 11 min readSharding, Replication, and Sharded Replication in Redisverything so far has assumed a single Redis instance. That's fine for a lot of use cases, but it has two hard limits: your dataset can't be bigger than one machine's RAM, and if that one machine goes syntax-soul.hashnode.dev
AAbstract AlgorithmsJul 2 · 1 min readSharding vs PartitioningDatabase scaling uses splitting strategies to handle massive datasets. While partitioning divides data within a single server, sharding distributes it across multiple nodes. 📊 Key Differences Partitiabstractalgorithms.hashnode.dev
SSandeep ChoudharyJun 28 · 8 min readDatabase Sharding - Strategies for Horizontal Data PartitioningWelcome back to our System Design Series! Today, we're diving deep into a crucial technique for scaling databases - sharding. As applications grow and data volumes explode, a single database instance sandeepc.hashnode.dev
AAwais AhmadJun 27 · 6 min readWhy Scaling Servers Doesn't Fix Your Database BottleneckHorizontal scaling solves many problems. But it doesn't solve all of them. One of the most common misconceptions among developers is that adding more application servers automatically means the applic2blog.itsahmadawais.com
