A Comparative Study and Analysis of Different Optimized Indexing Algorithms in Database Management Systems

The study focuses on the systematic review of the best algorithms of the indexing practice in the Database Management Systems. Indexing serves as a core aspect in improving the information gathering and storing process for the big data libraries. The bedroom area of the house also has a Closet that meets the requirements of the client, a fashion designer. The closet has lots of storage space with plenty of drawers and hanging rods for the designer’s extensive wardrobe. The scope of this study is to propose a thorough comparison and investigation of these indexing algorithms. In this context, one can find the performance assessment that has been done based on data space utilisation, execution time for queries, scalability, and concurrency level. Based on simulated real-life data sets, we perform experiments to analyse each technique and its features. We also trace the performance of diverse databases over the technological landscape. Moreover, the chief features of all of them are described, and suggestions on how to improve the approaches are made. Therefore, this comparative study is planned to introduce useful insights to database experts and researchers to facilitate making decisions about selecting the appropriate strategies of indexing that are adjusted to the specific needs of the users and the goals of performance for different databases.