Graduation Semester and Year
Summer 2025
Document Type
Thesis
Degree Name
Master of Science in Computer Engineering
Department
Computer Science and Engineering
First Advisor
David Levine
Second Advisor
Muhammad Rashed
Third Advisor
Faysal Hossain Shezan
Fourth Advisor
Remi Chou
Abstract
Storing and retrieving large amounts of data reliably is becoming more and more important as time goes on. There are high demands to store highly personal information such as social security numbers, bank account information, and residence information to rapidly changing data such as employee information, inventory information, and stock information. Therefore, the ability of a system to store, remove, and update such information efficiently and correctly is critical. There are different types of data that database systems can potentially hold: structured, unstructured, and semistructured data. Various database models have been developed to provide a framework that allows designers to translate the data they want to store, the relationships they want to capture between different data, and define the rules governing the data. These models offer unique advantages and disadvantages based on the type of data - structured, unstructured, or semistructured - that needs to be stored and the operations that need to be performed. Due to the fixed and predictable nature of structured data, structured data allows a variety of options in how a system can choose to store, manipulate, and retrieve such data. Furthermore, most systems, including the ones described above, tend to store structured data. The use of a primary key is one such method that is already used in most database systems with structured data. As this study will show, this method is effective, but does not help with queries that search for data using criteria that is not the primary key, such as age. This thesis will explore methods to improve operations that need to be done but are based on criteria other than the primary key.
Keywords
Database, Key, Structured Data, Shard
Disciplines
Computer and Systems Architecture | Data Storage Systems
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Haider, Neelim, "METHODS OF OPTIMIZING STORAGE AND RETRIEVAL OF STRUCTURED DATA" (2025). Computer Science and Engineering Theses. 533.
https://mavmatrix.uta.edu/cse_theses/533