The purpose of this research is to identify a way to bridge two query languages.  The two existing query languages used are structured query language (SQL) and regular expressions. Two different languages are used daily to search patterns, as well as, to retrieve data. SQL uses complex and powerful statements to retrieve data from structured data stores, such as, relational databases and enterprise data warehouses. Regular expressions, on the other hand, are used for searching unstructured data stores, such as, emails, web logs, Twitter feeds, and biomedical data.  This research examines ways to unify the querying of these disparate data stores. Nowadays, we spend hours or even numerous days querying a database for business decisions. The unification of two type of queries can be used to rapidly find answers, helping save money and energy resources. The development of a unified query language can make a contribution to the trend of zero waste. Zero waste is based on the idea of eliminating waste from processes through reuse and recycling. A unified query framework is expected to provide one-stop shop for real-time data analysis.