Question

A key factor that affects technology decisions is scalability. Define scalability. Explain the difference between high scalability, infinite scalability, and low scalability.

Answer 1

Scalability in technology is a general term used for any software platform or an algorithm which depicts the ability of the system to cope with the increase in the data size over a period of time. For example, if we talk about an np-hard or np complete problem it takes (Oⁿ²) time to compute any data point in it. If we apply some heuristics or metaheuristics to the problem which are in the form of an algorithm it gives the solution within a reasonable time. When we test the same heuristics for a larger dataset it should be able to produce the results again within the reasonable time, This ability of the algorithm or technology is called scalability. The machine learning algorithms used in current days are scalable enough to handle big-data.

High Scalability, Infinite scalability, and Low scalability

According to recent trends and research in IT sector, the scalability term focusses on two types of scalability one is high and another is low. High scalable technologies can handle an exponential increase of resources or the input data whereas low scalable technologies are sensitive to a small fold increase in the resources. High scale technologies produce the similar results with the high increment of data but low scalability means there is a near upper limit for the technology within which it works fine. Infinite scalability refers to a term where the technology platform can expand its paradigm according to change in the environment. But in actuality, there is no system which is infinitely scalable. Every technology has a threshold value beyond which it is difficult to get the output correctly.

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