A new method called Graphical Join (GJ) has been developed to speed up the process of combining data from multiple tables, which can be slow and resource-intensive in large databases. This approach uses special algorithms based on graphical models to summarize the joined data and then efficiently recreate the full results. In tests with different datasets, GJ has shown significant performance improvements over traditional methods like PostgreSQL, MonetDB, and Umbra. When performing joins in memory, GJ was 64 to 388 times faster than PostgreSQL and MonetDB and cut down on space requirements significantly. When handling joins on disk, GJ outperformed these systems by even greater margins, being up to 820 times faster than PostgreSQL and reducing space needs by thousands of times compared to MonetDB and Umbra.