What is necessary for data when converting to a cloud-based system?

In transitioning to a cloud-based system, scaling data horizontally is essential for several reasons. Horizontal scaling refers to the ability to add more machines or nodes to a system to handle increased load or data volume. This method allows cloud systems to effectively manage large datasets and facilitates better performance as demands grow.

When data is scaled horizontally, it enables a distributed architecture where resources can be allocated and balanced across multiple servers, enhancing fault tolerance and improving response times. This is particularly beneficial in cloud environments, where flexibility and scalability are crucial for accommodating variable workloads and ensuring efficient resource utilization.

As opposed to vertical scaling, which involves adding more power (CPU, RAM) to an existing machine, horizontal scaling ensures that the overall architecture can smoothly handle growth without being limited by single-point resource constraints. Thus, adopting a horizontal scaling strategy aligns well with cloud computing principles, supporting scalability, resilience, and efficiency in managing data.