Dogs have been the dearest friends of humans as guardians, companions and working partners for thousands of years. Since dogs are one of the most thoroughly domesticated animals, this has made them a long-term focus and perfect model for domestication genetics studies. Furthermore, their parallel evolution with humans has facilitated our understanding of human evolution itself. However, currently the most widely used dog single nucleotide polymorphism (SNP) dataset is from dbSNP (build139:ftp://ftp.ncbi.nlm.nih.gov/snp/, where ~80% of the ~2.7M SNPs were called from only two dogs, one Boxer(1) and one Standard Poodle(2). dbSNP only provides a total SNP list, combining SNPs from all samples, and does not have individual lists, which limits its usability in population genetic analysis. The rapid development of Next-Generation Sequencing (NGS) technology has facilitated the generation of massive dog/wolf genome datasets. However, SNP calling from the massive data generated by NGS is very laborious and requires a large amount of computational resources. This situation has promoted us to establish a canidae specific database (DoGSD) that focuses on whole genome SNP data from domesticated dogs and grey wolves. We collected SNPs from 2 unpublished dog/wolf genomes, 3 recently published works (3-5) that used 75 dog/wolf samples and the latest dog SNP dataset (dbSNP139). In total, DoGSD includes 8 grey wolves sampled from the Eurasian continent and America, 34 Chinese indigenous dogs from China, 34 breed dogs representing 5 breeds and 1 Dingo. Dogs from the 5 breeds include 11 German Shepherd dogs (Germany), 10 Kunming dogs (China), 11 Tibetan Mastiffs (China), 1 Belgian Malinois (Belgium), and 1 Basenji (Congo). The 34 Chinese indigenous dogs in our samples represent a key phase in dog domestication and are not included in any existing SNP database. DoGSD provides a powerful SNP retrieval interface that can extract data for each individual sample as well as a non-redundant dataset. SNPs are annotated to integrate information such as SNP-related genes, transcripts, proteins, and allows calculation of allele frequencies. DoGSD functionality includes the ability to search for gene-related synonymous and non-synonymous SNPs. In addition, we incorporate the essential genetic statistics viz. F- statistics (Fst) into DoGSD.