The fastest growing level of plant data sets over the past few decades is likely due to the application of next-generation sequencing as well as mass-spectrometry technologies to experimental model and plants research. The change in the volume and complexity of Omics (proteomics, transcriptomics, genomics, metabolomics) data creates challenges, mostly related to the collection, storage, and data sharing within the scientific community. The increase in data collection is limiting the existing computational connectivity and formal bioinformatics algorithms, which have become insufficient to accommodate gigantic-data inputs and analyzes. Several major challenges, such as the collection, analysis, visualizing, and storage of data sets, need to be tackled by modifying existing structures and creating new tools and databases for fast and efficient processing of big data. Many articles have been published in well know journals [3–6] (Tab: 1), which have collected the databases of different organisms and research area, e.g. “Biological databases for human research” have collected 74 human databases which have been published in Genomics Proteomics & Bioinformatics (GPB), “Online Databases for Taxonomy and Identification of Pathogenic Fungi and Proposal for a Cloud-Based Dynamic Data Network Platform” have collected 24 fungi databases and published in the journal of clinical microbiology, so that a well comprehensive plant database is also needed for the plant research community to sort and save all the plant data for future researchers, cause database of plants has been an integral part of modern biology. Enormous quantities of data are produced from plants   , such as protein functions in particularly sequences, MPIM database , P3DB , plant RNA database and website incorporates knowledge from numerous independent computer-assisted reaches and databases such as “PsnoRNA database” , “PceRBase database”  and “CSRDB” , The Pathway database is a database of biochemical pathways for metabolic, signaling, reaction and control[18, 19]. eg, “MetaCrop”, “PLaMoMdb”  while plant DNA database have genomic details of different plants, such as PLAZA , “Planteome” , “AtGDB” , According to such huge research, we have collected and integrated 225 far more popular and accessible plant databases from the most recent published lectures and created a well-known plant database (DBPR) that will be a convenient and friendly forum for the scientific community. Further, we have divided the plant database into five categories: DNA, RNA, Protein, Expression, and Pathway databases, which have three forms of searching option, browse by name or image expression, or search by name in the search bar. According to the published databases research work, many databases have been noticed in the different research area, which have been provided the latest database in the form of table[3–6]. Other hands, to make it’s easier and clearer to plant researchers we have provided the plant databases table as well as database, which is highlighted in the (Tab: 1) and will be updated over time.