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Horizontal scalability is the ability to increase capacity by connecting multiple hardware or software entities so that they work as a single logical unit.
When servers are clustered, the original server is being scaled out horizontally. If a cluster requires more resources to improve performance and provide high availability (HA), an administrator can scale out by adding more servers to the cluster.
An important advantage of horizontal scalability is that it can provide administrators with the ability to increase capacity on the fly. Another advantage is that in theory, horizontal scalability is only limited by how many entities can be connected successfully. The distributed storage system Cassandra, for example, runs on top of hundreds of commodity nodes spread across different data centers. Because the commodity hardware is scaled out horizontally, Cassandra is fault tolerant and does not have a single point of failure (SPoF).
Vertical scalability, on the other hand, increases capacity by adding more resources, such as more memory or an additional CPU, to a machine. Scaling vertically, which is also called scaling up, usually requires downtime while new resources are being added and has limits that are defined by hardware. When Amazon RDS customers need to scale vertically, for example, they can switch from a smaller to a bigger machine, but Amazon's largest RDS instance has only 68 GB of memory.
Scaling horizontally has both advantages and disadvantages. For example, adding inexpensive commodity computers to a cluster might seem to be a cost-effective solution at first glance, but it's important for the administrator to know whether the licensing costs for those additional servers, the additional operations cost of powering and cooling and the large footprint they will occupy in the data center truly makes scaling horizontally a better choice than scaling vertically.
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