A RDBMS is usually accessed using blocking drivers like JDBC/ODBC which require clients to block and wait for the result of each query they issue. An asynchronous database access mechanism would eliminate the need for such blocking and greatly improve client performance. Thread-Per-Connection and Thread Pooling are two methods currently being used to provide this asynchrony. This is inefficient since a lot of memory and computing power is spent in creating, scheduling and switching multiple threads. By these methods we cannot show how asynchronous database access can be achieved with a single thread using the Fork-Join mechanism which employs Future objects in Java. So, in this paper we propose an approach for automatically extracting embedded schemas from regular applications, e.g., written in java and automatically computing how schemas change as applications evolve. To showcase our approach, we perform a long-term schema evolution study. Our platform can be used for performing long-term, large-scale embedded schema evolution studies that are potentially beneficial to dynamic updating and schema evolution researchers.