<p>The exponential increase in digital data production is driving conventional storage technologies toward a critical threshold of inadequacy in terms of capacity, durability, and energy efficiency. This situation renders DNA based data storage systems, which stand out with their high information density and biochemical stability, a strategic alternative. The present review study systematically addresses DNA based storage technologies from an interdisciplinary perspective and comprehensively evaluates the integration between biotechnological processes and computer science. Based on the existing fragmentation in the literature, the “bio algorithmic interaction” between biochemical constraints and computational optimization models is analyzed as the main determinant of system performance. Within the scope of the study, DNA synthesis, PCR, and CRISPR based access mechanisms, as well as error correction, encoding, and data security strategies, are detailed. In particular, the effects of biochemical noise on system uncertainty are examined, and the structural distortions caused by synthesis errors in conventional encryption schemes based on the fixed length assumption are discussed. In this context, the critical importance of “device aware” algorithmic frameworks, in which hardware constraints are balanced with software intelligence, is emphasized. By analyzing the gaps in the current literature and the technical barriers, future research projections of the field are presented. As a result, the study reveals the necessity of hybrid structures in which metaheuristic optimization and biomolecular repair architectures are integrated, as well as international standardization, in order to enable the technology to be scaled to an industrial level.</p>