Ever been in a meeting where someone says, “Let’s shard the database!” — and half the team nods like it’s obvious?
Yeah. That’s the problem.
🧩 The Real Problem
Replication and sharding are not the same.
Yet, they often get tangled together in early scaling conversations.
- One scales reads.
- The other scales writes. Mix them up, and you’ll over-engineer your app or burn nights debugging latency that didn’t need to exist.
Developers keep asking the wrong question:
“Should we shard or replicate?”
The right answer?
You probably need both — but at different stages of growth.
⚙️ The Action (When to Use Each)
Here’s the quick mental model you should carry into your next sprint:
Replication: Copy the same data across multiple nodes. Great for read-heavy systems.
→ Perfect when your users start outnumbering your database connections.Sharding: Split your dataset across multiple servers. Great for write-heavy loads.
→ Use when your single-node writes start choking throughput.
Both are tools in your scaling toolkit — but each solves a distinct performance constraint.
🚀 The Solution (Stay Simple, Scale Smart)
Most apps don’t need sharding on day one.
If your Postgres instance still fits under 100GB and isn’t begging for mercy, sharding is premature optimization.
Start simple.
Vertically scale first.
Add replication when reads explode.
Shard only when writes become the bottleneck.
Build for today’s problem.
Architect for tomorrow’s.
That’s the short of it.
If you liked this breakdown, you’ll love the full version on CoreCraft — where we unpack complex backend topics with caffeine and curiosity.
Grab the full post 👉 Replication vs. Sharding: Stop Confusing Them
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