Carter Grove

Date of Award

12-2021

Document Type

Thesis

Degree Name

Master of Science in Systems Engineering

Department

Department of Systems Engineering and Management

First Advisor

Brent T. Langhals, PhD

Abstract

Industry and academia alike are more commonly using databases as solutions to advanced and complex problems. Unfortunately, not all database schemas are created equal and can yield different advantages in different areas. To try to understand what database schema might be best suited for a user’s needs, we sought out to distinguish how databases are measured against each other, what their performance characteristics are, and what advantages each type of database inherently possesses. To allow for the ingestion of data across the five different categories of database schemas, we used a met-analysis of past literature and aggregated the data to form the basis of data to analyze. The data was then used to compare which database schemas exhibited the best performance for accuracy, scalability, transactions, query latency, and writing latency. After analyzing the data, a mix of NoSQL databases performed the best for scalability, transactions, and query and writing latency, making them advantageous for database solutions for unique problems. Relational databases maintained the best accuracy among databases and are the cheapest solution, making them suitable for basic databasing needs. Most importantly, many applications will require some degree of individualized investigation to understand what schema would be best suit.

AFIT Designator

AFIT-ENV-MS-21-D-047

DTIC Accession Number

AD1157179

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