For the past decades, the computing power in High Performance Computing (HPC) grows doubled every 1.8 years and we will soon face the exa-scale (10^18 operation per second) computing era. However, the IO-related technology will not scale to face with the growth of computing powers and, in fact, it has been a serious bottleneck in many scientific applications. Especially, in big data science, seeking scientific breakthroughs from large-scale data analysis in the fields of physics, cosmology, biology, to name a few, IO performance is a critical issue. Our research focus is to provide cutting-edge IO performance for scientific applications and help scientists to achieve scientific breakthroughs. In the line of this effort, we have developed the Adaptable IO System (ADIOS), a simple and flexible IO middleware designed to orchestrate various IO components and harness application performance for large-scale and data-intensive scientific applications. ADIOS has been successfully applied in many real-world scientific applications, such as Gyrokinetic Toroidal Code (GTC), plasma fusion simulation code (XGC), combustion simulation code (S3D), and proved its success by showing increased IO performances.