The major objective of this paper is to present Big Data Storage techniques and Data Virtualization. The Data virtualization servers have focused on making big data processing easy. They can hide the complex and technical interfaces of big data storage technologies, such as Hadoop and NoSQL, and they can present big data as if it is stored in traditional SQL systems. This allows us as developers to use our own existing skills and to deploy our traditional ETL, reporting, and analytical tools that all support SQL. Additionally, the products and our existing skills can extend the data security mechanisms for accessing and processing big data across multiple big data systems. But with scale and performance rising, making big data processing is not enough and easy anymore. As such, the next challenge for data virtualization is parallel to big data processing. In this paper, All of the above regular issues are covered in my paper along with their proper prospects.