The XData system, currently being developed at IIT Bombay, provides an automated and interactive platform for grading student SQL queries, as well as for learning SQL. Prior work on the XData system focused on generating query specific test cases to catch common errors in queries. These test cases are used to check whether the student queries are correct or not. For grading student assignments, it is usually not sufficient to just check if a query is correct: if the query is incorrect, partial marks may need to be given, depending on how close the query is to being correct. In this paper, we extend the XData system by adding features that enable awarding of partial marks to incorrect student queries. Our system is able to go beyond numerous syntactic features when comparing a student query with a correct query. These features of our grading system allow the grading of SQL queries to be fully automated, and scalable to even large class sizes such as those of MOOCs.