Classical databases represent the traditional RDBMS's and the most widely used RDBMS in the world of databases and information systems; they have been regarded as the best systems for managing data. Today with the growth of the applications and data consumers, and its openness to the general public, tradi- tional Databases are not able to meet the needs of a large number of applications, including OLAP data processing and Business Intelligence analysis; As a result, many variants of DBMS have emerged like: Column Store, In Memory and NOSQL Databases, that meet users' expectations well, and which are better adapted to cur- rent needs. As a result, the scope of classical databases has become increasingly restricted to handle OLTP models and other few models. To deal with this prob- lem, vertical fragmentation is the best way to effectively handle the OLAP model, but this technique fails to handle some analytical queries with low selectivity, pre- senting poor results in some cases. In this perspective, we propose a new vertical fragmentation design T-Plotter which makes it possible to deal effectively with the whole of analytical queries and improve the performance of RDBMSs to process the OLAP data models.
