DNA sequencing is the process of determining the precise order of nucleotides (A, C, G, T) within a DNA molecule and is now indispensable for genetics and medical research. Next-generation sequencing (NGS), in which short DNA fragments can be sequenced in a massively parallel fashion, enables high-throughput sequencing . However, the succeeding data analysis, also known as DNA mapping, is excessively time consuming. DNA mapping can be partitioned into Suffix Array (SA) Sorting and Backward Searching. Dedicated hardware designs have been proposed to enhance the speed, but only for the less complex Backward Searching . Feasible hardware for the most complicated part, SA sorting, has never been explored. This work presents a fully integrated NGS data processor that realizes both SA sorting and Backward Searching. The distributed sort algorithm is utilized to reduce the sorting complexity. The throughput of SA sorting is maximized through 2,048 insertion-sorting elements. Dedicated overflow and splitter caches are embedded to reduce the computation latency. With the optimized hardware architecture, the NGS processor achieves orders of magnitude improvement in both energy and throughput metrics compared to the high-end generic processors.