Bloom Filters for Efficient Coupling Between Tables of a Database

Nowadays, digital data are the most valuable asset of almost every organization. Database management systems are considered as storing systems for efficient retrieval and processing of digital data. However, effective operation, in terms of data access speed and relational database is limited, as its size increases significantly [6]. Bloom filter is a special data structure with finite storage requirements and rapid control of an object membership to a dataset. It is worth mentioning that the Bloom filter structure has been proposed with a view to constructively increase data access in relational databases. Since the characteristics of a Bloom filter are consistent with the requirements of a fast data access structure, we examine the possibility of using it in order to increase the SQL query execution speed in a database. In the context of this research, a database in a RDBMS SQL Server that includes big data tables is implemented and in following the performance enhancement, using Bloom filters, in terms of execution time on different categories of SQL queries, is examined. We experimentally proved the time effectiveness of Bloom filter structure in relational databases when dealing with large scale data.