In these days to enhance the performance of databases researchers propose compression as well as query optimization. Compression reduces volume of data and query optimization reduces execution time of query. There are some issues while compressing database and performing query optimization the first one is the selection of suitable compression scheme. Second is how to reduce the query execution time. which algorithm we use. How to overcome on the demerits of these two issues. We use dictionary-based approach for compression with many small dictionaries that quickly load in the memory on demand. One big diction requires more time for loading and scanning. We also perform query optimization on database without decompressing it by considering fewer execution plans instead of all. The use of many small - dictionaries save space, load quickly. Due to compression, smaller size of intermediate results, less I/O operation required and less buffer misses occurs. While in query optimization selection of randomized algorithm with enhancement consider fewer execution plans instead of all plans. This reduce query execution time. We conclude that the use of compression and query optimization improve the performance of database.