Hymenopteran venoms contain diverse proteins and peptides that shape envenomation, defense, predation, and allergic responses. Honeybee venom from Apis mellifera is well characterized, while molecular resources for the Asian giant hornet Vespa mandarinia remain less curated. We compared protein- and peptide-fraction LC-MS/MS identification datasets from V. mandarinia venom (VM-V) and A. mellifera venom (AM-V), supported by a de novo V. mandarinia transcriptome-derived database. Protein-level identification yielded 197 protein groups in VM-V PRO and 164 protein groups in AM-V PRO. AM-V contained well-recognized honeybee venom components, including phospholipase A2, hyaluronidase, venom acid phosphatase, venom dipeptidyl peptidase 4, melittin precursor, mast cell degranulating peptide precursor, secapin, and allergen Api m 6. VM-V PRO contained transcriptome-supported candidate venom-associated proteins, including venom dipeptidyl peptidase 4-like, hyaluronidase-like, venom allergen 5-like, serine protease-like, apolipophorin-like, and hexamerin-like entries. Peptide-fraction annotation was strongest in AM-V PEP, led by melittin precursor, whereas VM-V PEP remained largely unannotated. The study focuses on identification, annotation, and hypothesis-generating functional summaries, not replicate-level differential abundance. GO, KEGG, and STRING analyses organized functional annotation patterns and prioritized candidate protein groups. These data provide an identification-based comparative venomomics resource for VM-V and AM-V and a foundation for targeted validation of candidate V. mandarinia venom-associated components.