Figueiredo, FigueiredoCardoso, FilipeSaraiva, GoncaloRebelo, JoãoRodrigues, RicardoWanzeller, CristinaMartins, PedroAbbasi, Maryam2024-01-102024-01-102023Figueiredo, D., Saraiva, G., Rebelo, J.,Rodrigues, R., Cardoso, F., Wanzeller, C., Martins, P. & Abbasi, M. (2023). Performance Evaluation Between HarperDB, Mongo DB and PostgreSQL. In J. L. Reis, M. Del Rio Araujo, L. P. Reis, J.P.M. dos Santos (Eds), Marketing and Smart Technologies. ICMarkTech 2022 : Vol. 344. Smart Innovation, Systems and Technologies (pp. 85–94). Springer, Singapore. https://doi.org/10.1007/978-981-99-0333-7_7978-981-99-0333-7http://hdl.handle.net/10400.15/4675Several modern-day problems, like information overload and big data, need to deal with large amounts of data. As such, to meet the application requirements, for instance, performance and consistency, more and more systems are adapting to the specificities. The existing Relational Database Management System (RDBMS)’s the processing of massive data has become an issue because these databases do not deal with a massive amount of data. NoSQL is a database management system that makes processing massive and/or unstructured data easier because it uses key-value to store the data, collections or document stores instead of tables. Many companies today tend to start a project using NoSQL. However, HarperDB aims to produce a relational and nonrelational DBMS, allowing developers to choose between different solutions. This paper aims to show the most relevant differences between HarperDB, MongoDB and PostgreSQL and compare their performances. Preliminary results show that PostgreSQL performs better with structured data, but HarperDB can integrate NoSQL and SQL, which can be a significant advantage to HarperDB compared to the other solutions.engRDBMSNoSQLPostgreSQLMongoDBHarperDBPerformancebook parthttps://doi.org/10.1007/978-981-99-0333-7_7