Abstract: Rice (Oryza sativa L.) is both a major staple food and a model crop plant for monocot studies. Facing the increasingly severe environmental and population problems, breeding varieties with high yield, high quality, and wide adaptability is the efficient way to solve the food security problems. With the rapid development of multi-omics technology, large volumes of data related to rice genetics and breeding have been accumulated. Bioinformatics databases and online analysis tools are developed to store, integrate, visualize, and share these datasets. In addition, some databases possess built-in tools for further mining and using datasets to provide data support for decision-making in breeding. In this review, we systematically sort out rice bioinformatics databases and online analysis tools developed in the past two decades. Subsequently, we classified and summarized these resources based on their built-in datasets and features. Finally, the problems and deficiencies of the existing rice bioinformatics resources were discussed, and the development direction of bioinformatics resources in the era of big data and artificial intelligence was prospected.