The Study Of Data Modeling Methodologies For Column-Oriented Databases

Further research regarding databases suggest that applying data modeling in NoSQL databases as in SQL databases could improve its performance. This discovery leads to the birth of many research regarding methodologies for data modeling in NoSQL databases, including ones for column-oriented databases. Two column-oriented databases data modeling methodologies that were discussed in this research that use EER diagrams for their conceptual models are Chebotko methodology which also considers application queries for its database and Poffo methodology which depends only on its EER diagrams. Thus, the purpose of this research is to analyze the difference between both data modeling methodologies in column-wide oriented databases. The testing results show that on the chosen case study, the physical data model made using Chebotko methodology causes queries to retrieve data 2.24 times slower than the ones made using Poffo methodology. In conclusion, modeling data in column-oriented databases using Poffo methodology is generally safer because the size of its corresponding column families could remain small, whereas one would have to exercise caution while modeling data using Chebotko methodology because the column families created could be too big due to inquiring too much information in a query.