An Investigation into the Efficiency of Specific Databases for Tracking Purposes in Scope of IT Startup
Volodymyr Franiv, S. V. Vasylyuk, Oleksandr R. Biletskyi, Ihor Franiv · 2023
This science paper presents a comparative analysis of the performance of a location tracking application developed by our team using the ASP.NET framework. The study focuses on evaluating the application's performance based on different databases utilized for storing and retrieving location coordinates from multiple resources. The databases examined in this research include MySQL, MSSQL, PostgreSQL, Redis and MongoDB, representing a mix of relational and non-relational databases. The primary objective of this investigation is to offer guidance to startups faced with the decision of selecting an optimal database solution for tracking tasks within their projects. Given the resource limitations typically encountered by IT startups, maximizing database performance in terms of storing and managing data is of paramount importance. Throughout the study, various performance metrics were measured and compared for each database option. By thoroughly assessing the performance of the application under different database, we aim to provide valuable insights into which database type would be most suitable for specific tracking tasks in startup projects. The results of this analysis shed light on the strengths and weaknesses of each database, highlighting the potential trade-offs that startups might encounter when choosing a particular database for their tracking applications. Ultimately, the findings presented in this article aim to empower startups in making informed decisions that align with their specific project requirements, ensuring they can leverage the maximum performance from their selected database while efficiently managing stored data.