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SUMMARY: We have developed a compendium and interactive platform, named Stress Combinations and their Interactions in Plants Database (SCIPDb; http://www.nipgr.ac.in/scipdb.php), which offers information on morpho‐physio‐biochemical (phenome) and molecular (transcriptome and metabolome) responses of plants to different stress combinations. SCIPDb is a plant stress informatics hub for data mining on phenome, transcriptome, trait‐gene ontology, and data‐driven research for advancing mechanistic understanding of combined stress biology. We analyzed global phenome data from 939 studies to delineate the effects of various stress combinations on yield in major crops and found that yield was substantially affected under abiotic–abiotic stresses. Transcriptome datasets from 36 studies hosted in SCIPDb identified novel genes, whose roles have not been earlier established in combined stress. Integretome analysis under combined drought–heat stress pinpointed carbohydrate, amino acid, and energy metabolism pathways as the crucial metabolic, proteomic, and transcriptional components in plant tolerance to combined stress. These examples illustrate the application of SCIPDb in identifying novel genes and pathways involved in combined stress tolerance. Further, we showed the application of this database in identifying novel candidate genes and pathways for combined drought and pathogen stress tolerance. To our knowledge, SCIPDb is the only publicly available platform offering combined stress‐specific omics big data visualization tools, such as an interactive scrollbar, stress matrix, radial tree, global distribution map, meta‐phenome analysis, search, BLAST, transcript expression pattern table, Manhattan plot, and co‐expression network. These tools facilitate a better understanding of the mechanisms underlying plant responses to combined stresses. Significance Statement: SCIPDb is a publicly available platform that enables students and researchers to understand how different combined stresses affect plant morpho‐physiological and molecular responses. The database focuses on phenomics and provides a valuable resource for researchers. By analyzing combined stress‐specific transcriptomics and metabolomic datasets, SCIPDb offers new biological insights into gene discovery. Our experimental work based on candidates revealed from the database has demonstrated the discovery of novel genes and pathways specific to combined stress. [ABSTRACT FROM AUTHOR]