Recent advancements in single-cell RNA sequencing (scRNA-seq) technology haveenabled the comprehensive profiling of gene expression patterns at thesingle-cell level, offering unprecedented insights into cellular diversity andheterogeneity within plant tissues. In this study, we present a systematicapproach to construct a plant single-cell database, scPlantDB, which is publiclyavailable at https://biobigdata.nju.edu.cn/scplantdb. We integrated single-celltranscriptomic profiles from 67 high-quality datasets across 17 plant species,comprising approximately 2.5 million cells. The data underwent rigorouscollection, manual curation, strict quality control and standardized processingfrom public databases. scPlantDB offers interactive visualization of geneexpression at the single-cell level, facilitating the exploration of bothsingle-dataset and multiple-dataset analyses. It enables systematic comparisonand functional annotation of markers across diverse cell types and species whileproviding tools to identify and compare cell types based on these markers. Insummary, scPlantDB serves as a comprehensive database for investigating celltypes and markers within plant cell atlases. It is a valuable resource for theplant research community.