Big data has raised the bar for data virtualization products! Until now 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’s stored in traditional SQL systems. This allows developers to use their existing skills and to deploy their  traditional ETL, reporting, and analytical tools that all support SQL. Additionally, the products 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 easy is not enough anymore. As such, the next challenge for data virtualization is parallel big data processing.