With larger shares of renewable energy sources in the generation mix, their inherent variability and intermittency increasingly challenge power system stability. One strategy to mitigate the variability of renewable energy sources is to co-locate complementary energy sources. This article reviews the concept of renewable energy complementarity, with a particular focus on metrics for complementarity assessment. Twelve distinct metrics are identified and classified into four groups: statistical, fluctuation-based, event-based, and effectiveness metrics. Of the reviewed articles, approximately one-third employed the Pearson correlation coefficient, and more than half focused on wind-photovoltaic (PV) combinations. The identified metrics are compared in this study using both synthetic test data and meteorological reanalysis data. Our analysis reveals that metrics designed for more than two sources tend to overestimate complementarity, and no single metric consistently captures all relevant aspects. We recommend the combined use of multiple metrics, chosen for the intended application, to ensure a robust and transparent assessment.