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The integration of multiple ‘omics’ datasets is a promising avenue for answering many important and challenging questions in biology, particularly those relating to complex ecological systems. Whereas, multi-omics was developed using data from model organisms with significant prior knowledge and resources, its application to non-model organisms, such as coral holobionts, is less clear-cut. We explore, in the emerging rice coral model Montipora capitata, the intersection of holobiont transcriptomic, proteomic, metabolomic, and microbiome amplicon data and investigate how well they correlate under high temperature treatment. Using a typical thermal stress regime, we show that transcriptomic and proteomic data broadly capture the stress response of the coral, whereas the metabolome and microbiome datasets show patterns that likely reflect stochastic and homeostatic processes associated with each sample. These results provide a framework for interpreting multi-omics data generated from non-model systems, particularly those with complex biotic interactions among microbial partners.