High-throughput sequencing data, such as target capture, RNA-Seq, genome skimming, and high-depth whole-genome sequencing, are used for phylogenomic analyses. Integrating these mixed data types into a single phylogenomic dataset requires several bioinformatic tools and significant computational resources. Here, we present Captus, a novel pipeline to analyze mixed data efficiently. Captus assembles these data types, searches for loci of interest, and produces paralog-filtered alignments. If reference target loci are not available for the studied taxon, Captus can also be used to discover new putative homologs via sequence clustering. Compared to other software, Captus allows the recovery of a greater number of more complete loci across more species. We apply Captus to assemble a comprehensive dataset, comprising the four types of sequencing data for the angiosperm order Cucurbitales, a clade of about 3,100 species in eight mainly tropical plant families, including begonias (Begoniaceae) and gourds (Cucurbitaceae). Our phylogenomic results support the currently accepted circumscription of Cucurbitales except for the position of the holoparasitic Apodanthaceae, which group with Rafflesiaceae in Malpighiales. A subset of mitochondrial gene regions supports the earlier divergence of Apodanthaceae in Cucurbitales. However, the nuclear regions and the majority of mitochondrial regions place Apodanthaceae in Malpighiales. Within Cucurbitaceae, we confirm the monophyly of all currently accepted tribes but also reveal hybridization and incomplete lineage sorting both in Cucurbitales and within Cucurbitaceae. We show that contradicting results among earlier phylogenetic studies in Cucurbitales can be reconciled when accounting for gene tree conflict and demonstrate the efficiency of Captus for complex datasets.