We have cross checked with industry standard tools like pganalyze. Most them analyze the workloads in isolation. There are no continuous evaluations and context carry forward across the runs.

DeepSQL does continuous evaluation of queries, we maintain performance life cycle of a query by customer.

A dashboard query for customer A might run for 2s, but for customer B it would take 50s. Here data clustering is the problem, skewness of distinct join keys … various factors. If query fix has to happen by looking at that query alone, one would make wrong decision (probably creating index). But a holistic decision would be partitioning here.