In this study, we investigate the heterogeneity in energy and non-energy commodities by analyzing their four realized moments: returns, realized volatility, realized skewness and realized kurtosis. Utilizing monthly data, we examine two commodity categories over various crisis periods. This study examines a comparative approach to descriptive statistics across different crisis periods and the full sample and assesses the out-of-sample significance of heteroscedasticity using GARCH models. The findings reveal significant heterogeneity in both energy and non-energy commodities, with energy commodities exhibiting higher average returns and volatility. Crisis periods markedly influence the statistical properties of these commodities. GARCH models outperform ARMA models in forecasting realized moments, particularly for non-energy commodities. This research contributes to the literature by providing robust evidence of heterogeneity in commodity markets and highlights the importance of considering all four realized moments in such analyses.