# Replication & Sharding — System Design: Architecture, Scale and Trade-offs

Source: https://www.skillbyai.com/en/system-design/sd-replication-sharding

> Scale reads with replication and writes with sharding, and pick shard keys that avoid hotspots.

## Replication

Keep copies of the same data on multiple nodes. A **primary** takes writes and streams them to **replicas** that serve reads and stand by for failover.

## Sharding (partitioning)

Split one dataset across nodes by a **shard key** (e.g. user_id hash or range). Each shard holds a slice, so writes and storage scale out.

## Pick the shard key carefully

A bad key creates hotspots (e.g. sharding by date puts all of today's writes on one node). Aim for even distribution and queries that hit one shard.

**Quiz:** Your database is bottlenecked on write throughput. What helps most?

- [x] Shard the data
- [ ] Add read replicas
- [ ] Add a bigger cache
- [ ] Switch to a larger CDN

*Answer:* Shard the data. Replicas and caches scale reads. Sharding spreads writes across nodes.