Statistical power and p values are both quantitative indexes.
The statistical power of a test is the probability of rejecting a false null hypothesis, while a p value is the probability of a given result assuming the null hypothesis of no effect is true.
Statistical power and p values are similar in the sense that both are related to the effect size being sought and the sample size. But they are fundamentally different metrics.
A p value reflects the chosen level of alpha, while statistical power is related to beta. In other words, the former quantifies the probability of making a Type I error, while the latter quantifies the probability of making a Type II error.
Further reading:
Effect Size FAQs 