Performance Analysis of Neo4j, MongoDB, and PostgreSQL on 2019 National Election Big Data Management Database

Data has now become a major commodity and asset for any organization. There's also a phenomenon called Big Data where it's a term to describes a large volume of data, both structured and unstructured. With big data, any organization can analyze the data and its results are used for decision making and business strategy. Political parties, for example, use it to analyze the likelihood of their candidate winning in the election based on voter data who votes for their candidate. In Indonesia itself, the use of big data has not been utilized because of limited database infrastructure. Therefore, Indonesia needs a good database that can utilize big data. In this study, the author examines the performance of PostgreSQL, MongoDB, and Neo4J by analyzing each of its complexity using computational complexity theory with Big O notation as its tool. With Big O, the author measures the complexity of each execution time. The conclusion from this study is that MongoDB has excellent performance because it has an O(1) complexity, PostgreSQL has good performance because it has an O(n) and O(1) complexities, and Neo4j has worse performance than MongoDB and PostgreSQL because it has an O(nlog n) complexity.