From deep archival to real-time applications: Challenges and opportunities in DNA data storage

DNA has emerged as a highly promising next-generation data storage medium, offering unprecedented density, long-term durability, and low energy consumption compared to conventional storage technologies. Despite rapid advances, significant challenges remain across the entire spectrum of data storage scenarios-ranging from deep cold archival storage to hot, real-time data processing. For deep cold data, where data may not be accessed for decades, the primary requirements are extremely long-term preservation and maximized physical information density. Strategies such as silica encapsulation, porous photonic microspheres, and robust microbial chassis have demonstrated theoretical storage lifespans of centuries to millennia. In cold data scenarios, where files are accessed periodically, the ability to perform random access and repeated retrievals without data loss is critical. Advances in molecular indexing, microfluidic partitioning, and low-bias isothermal amplification offer promising solutions, while cellular systems provide a low-cost platform for repetitive readouts via high-fidelity replication. Warm and hot data storage presents the greatest technical barriers, including insufficient read/write throughput, high latency, and the lack of native support for dynamic data operations. Bridging this gap requires integration with automated, scalable molecular systems and further improvements in speed and reusability. Therefore, enabling the practical application of DNA storage across deep cold, cold, warm, and hot data scenarios will require sustained interdisciplinary efforts in molecular design, storage media engineering, and data retrieval strategies, along with system-level integration to meet the diverse demands of long-term durability, random access, and real-time responsiveness.