Horizontal vs. Vertical Scaling in the Cloud

Horizontal vs. Vertical Scaling in the Cloud

When a business starts to grow, it should be as flexible as possible. As your app scales, it will accelerate your growth, improve user experience, and reach a wider audience. Basically, scalability allows you to better manage your application and adapt to new requirements. When building a growth strategy for your business, building a scalable application should be one of the first priorities.

The question “which is better: vertical or horizontal scaling?” does not lose its relevance.

Let’s start with what is scalability in cloud computing. That means the capability to advance and cut down the volume or performance of a solution fast and easy. Some cloud platforms are designed to scale automatically.

Scaling types

The main and most common types of scaling procedures include:

  • Vertical scaling

Scaling up is when the overall power of a business is increased by improving the performance of the server’s internal resources — processor, memory, disk, and network capacity. The server in its basic form remains unchanged.

Scaling up assumes increasing server capacity. The main advantage of the method is its simplicity. There is no need to rewrite code when additional capacity is added, and it is much easier to manage one large server than an entire system. This is also the main disadvantage: scaling the resources of one server has very specific hardware limitations. It is also worth considering the cost of such a solution: a server with a multiple of the amount of computing resources in most cases turns out to be more expensive than several less powerful servers that add up to such performance.

  • Horizontal scaling

In particular, as the digital load and traffic is constantly growing, vertical scaling will sooner or later face limitations in the form of server technical specifications. And this is where horizontal scaling comes into play. The main meaning of this term is that computing power is increased by adding identical nodes on top of existing ones. Scale out is most often achieved when there is a configured server infrastructure (in particular, data centers), as well as a consistent communication scheme between servers.

Scaling out means increasing performance by splitting data across multiple servers. This method assumes an increase in performance without compromising fault tolerance.

There are three main types of horizontal scaling:

1. Replication. This term refers to the copying of data between servers.

2. Partitioning. This scaling method consists in dividing the data into parts according to some attribute.

3. Segmentation. It is a database design principle in which parts of a table are stored separately on different physical servers. Segmentation is the most suitable solution for large-scale operations, especially when paired with replication. But it is worth noting that this is quite difficult to organize, since it is necessary to take into account server-to-server communication.

  • Diagonal scaling

This is a relatively new term. Diagonal scaling brings together the best of both worlds and defines the vertical scaling of scale-out nodes that are already implemented in existing server infrastructure.


Based on the foregoing, it would be incorrect to contrast these two types of scaling. After all, each of them has its own advantages and limitations, but now you can not choose, but enjoy the benefits of both types, combining them.

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