Is cost always inversely proportional to performance?

Typically, higher performance is associated with higher costs. Spark provides options for tunable performance and cost. At a high level, it is a given that if your end-to-end latency is stringent or low, then your cost will be higher.

But using Delta to unify all your workloads on a single platform brings efficiencies of scale through automation and standardization, leading to cost reductions by reducing the number of hops and processing steps, which translates to a reduction in compute power. Also, when your queries run faster on the same hardware, you pay for a shorter duration of your running cloud computing cost. So yes, it is possible to improve performance and still contain the cost. SLA requirements are not compromised. Instead, superior architecture options are available, such as the unification of batch and streaming workloads, handling both schema enforcement alongside schema evolution, and the ability to handle unstructured...