DPDK Summit 2025

With Increase of high performance data applications require data to written at very high speeds , where traditional Row based systems struggle with the scale and complexity of data. This session explores the usage of DPDK and kernel bypass techniques to massively improve the throughput of I/O operations when scaling in order of PetaBytes. Gives insights and key decisions and trade offs while building and implementing such systems. Using DPDK to enhance parallel writing of nested data in columnar formats at petabyte scale combines the framework’s high-performance ethos with the needs of modern data systems. By leveraging DPDK’s multi-threading, memory management, and hardware acceleration, this approach removes traditional bottlenecks, enabling scalable, efficient data storage for applications from scientific research to big data analytics. As data volumes grow, acceleration techniques are very key to improve efficiency and scaling the system.