# Horizontal vs Vertical Scaling

URL: https://softwaredictionary.org/compare/horizontal-vs-vertical-scaling
Last updated: 2026-10-03

In short: Horizontal scaling adds more machines and spreads the load across them, while vertical scaling gives one machine more CPU, memory or faster storage.

## What is the difference between horizontal and vertical scaling?

When a system runs out of capacity, there are two directions to grow. Scaling up, or vertically, means moving to a bigger server: more cores, more memory, faster disks. Scaling out, or horizontally, means running more servers side by side, with a load balancer sharing the work between them.

Vertical scaling is the simplest: the application doesn't change, and a single machine avoids the complexity of distributed systems. It suits databases and software that are hard to split. But every machine has a maximum size, the largest ones are disproportionately expensive, upgrades may need downtime, and one machine is a single point of failure.

Horizontal scaling can grow almost without limit and tolerates failures, because losing one instance leaves the others running, and it allows rolling updates without downtime. It requires stateless application servers that keep sessions and files in shared services, and for databases it means replication and sharding, which add real complexity.

A common misconception is that horizontal scaling is always the modern, correct choice. Many successful systems scale vertically first, because it is cheap in engineering time, and scale out only the parts that need it. In practice the two are combined: a few large database servers and many small, stateless application servers.

| Aspect | Horizontal Scaling | Vertical Scaling |
| --- | --- | --- |
| How | Add more machines | Make one machine bigger |
| Also called | Scaling out | Scaling up |
| Limit | Practically unlimited | The largest available machine |
| Fault tolerance | High: other instances keep running | Low: one machine is a single point of failure |
| Application changes | Often needed: statelessness, sharding | Usually none |
| Downtime to scale | None with rolling changes | Often a restart |
| Fits | Stateless web and API servers | Databases and hard-to-split software |

## Choose Horizontal Scaling when

- Traffic grows beyond what one machine can handle.
- You need high availability and zero-downtime updates.
- Your application servers are, or can be made, stateless.

## Choose Vertical Scaling when

- You want the quickest fix with no code changes.
- Your system, such as a relational database, is hard to distribute.
- Growth is moderate and a bigger machine is enough.

## Frequently asked questions

**Which is cheaper, horizontal or vertical scaling?**

Vertical scaling is cheaper in engineering effort at first. At large scale, many smaller machines are usually cheaper than one huge one, and they also add resilience.

**Do databases scale horizontally?**

They can, but with more effort: read replicas spread reads, and sharding spreads writes across servers. Some distributed databases are designed to scale out from the start.

**What does autoscaling do?**

It scales horizontally automatically, adding instances when load rises and removing them when it falls, based on metrics such as CPU use or request rates.

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