Sharding: Splitting Data Across Servers
There comes a point for very large systems where a single database server simply cannot hold or serve all the data fast enough. Sharding is the technique of splitting that data across several servers so each handles a manageable slice.
It is powerful but adds real complexity, so we treat it as an advanced step taken only when simpler options are exhausted.
How Sharding Works
Data is divided by a chosen key — for example, customer ID or region — and each shard holds one range of values. An application then directs each query to the shard that owns the relevant data.
The Trade-Offs
- Queries that span shards become harder and slower.
- Choosing a poor shard key can create 'hot' servers.
- Backups, migrations and reporting all grow more complex.
Simpler Steps First
- Optimise queries and add the right indexes.
- Add read replicas to spread read load.
- Move to a larger server (vertical scaling).
- Consider sharding only once these are no longer enough.
Frequently Asked Questions
Will my project need sharding?
Almost certainly not unless you reach very large scale. The vast majority of business systems never require it.
If you need a hand with any of this, your Progressive Robot delivery team is ready to help. Raise a ticket from the Support area of your client portal or speak to your account manager and we will guide you through the next steps.