Horizontally Scalable
Horizontally scalable refers to the ability of a system to increase its capacity by adding more machines or nodes to the network. In data science and artificial intelligence, horizontally scalable systems are essential for handling large amounts of data and processing power required for complex algorithms. This type of scalability is achieved by distributing the workload across multiple machines, allowing for increased processing power and storage capacity. Horizontally scalable systems are designed to handle high traffic and large datasets, making them ideal for big data applications and machine learning models. By adding more machines to the network, horizontally scalable systems can handle increased demand without sacrificing performance or reliability.
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