Relational databases scattered over the web are generally opaque to regular web crawling tools. To address this concern, many RDB-to-RDF approaches have been proposed over the last years. In this paper, we propose a detailed review of RDB-to-RDF methods and tools, considering end-to-end projects that delivered operational tools. The different approaches are classified along four major axes: motivation of the approach; mapping description language and expressiveness; mapping implementation; and data retrieval method. Then, we analyse commonalities and differences between existing approaches, and we underline common patterns in the orchestration of solutions applicable to each step of the translation process. Finally, we underline that the expressiveness of existing mapping languages is not always sufficient to produce rich semantic data and make it usable, interoperable and linkable. We therefore briefly present various strategies investigated in the literature to produce additional semantic data.