Process optimization in ring rolling is crucial for achieving resource efficiency, competitiveness and the enabling of new products and process strategies. To gain an overview for data-centric optimization approaches and its utilized databases, a systematic literature review is presented. Major aspects of the review are to identify the data generation method, the strategy for this, the regarded process and the underlying optimization. Moreover, the literature has been screened for machine learning applications, a novel approach within ring rolling. The focus in the analysis is set on the utilized databases for optimization and machine learning, especially the data generation and the data sources. Based on the found results, future challenges and possible trends are discussed. The presented review gives a comprehensive overview to display current data-centric trends in ring rolling and aims to provide a foundation for data generation methods for optimization and the application of machine learning.