Legumes, and especially pulses, are an important source of protein for food and feed, and are appreciated for their positive impact on the “one health”. However, their unstable yields and their susceptibility to biotic and abiotic stresses highlight the need for varietal improvement in order to increase the cultivated areas and productivity. With the advent of sequencing technologies, a large pool of genetic and -omic resources, heterogeneous at the inter- and intraspecies scale, is emerging. Thus, it is important to capitalize on these scattered heterogeneous data to develop translational research and boost breeding projects and crop diversification. To meet this need, we undertook the development of NeoLeg, a NoSQL graph-based database using Neo4j, dedicated for translational research in pulses. Starting from genome sequences and annotation files, we inferred orthologous relationships between genes, and proposed associated syntenic blocks between the chromosomes of four cultivated crops, namely Pisum sativum, Vicia faba, Lens culinaris and Vigna radiata, and model legume Medicago truncatula. Available information on quantitative trait loci (QTL) for multiple traits are being included as well as expression data. The proposed modeling was evaluated in studying the conservation of a flowering-promoting gene. The main achievements as well as remaining challenges and perspectives will be discussed