Optimizing a real-life database based on workload evolution: a comparative analysis of SQL and NoSQL approaches

This study performs a dynamic cost-benefit analysis of migrating the Sloan Digital Sky Survey (SDSS) SkyServer database to optimized SQL and NoSQL schemas based on its workload evolution. Utilizing data spanning over two decades, the research explores the adaptation of database schemas at three pivo...

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Detalhes bibliográficos
Autor: Zarate Calderon, Gabriel
Formato: tesis de maestría
Fecha de publicación:2024
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/415743
Acesso em linha:https://hdl.handle.net/2117/415743
Access Level:acceso abierto
Palavra-chave:SQL (Computer program language)
Embedded computer systems
Dynamic Cost-Benefit Analysis
Database Migration
SQL Schemas
NoSQL Schemas
Schema Optimization
Workload Evolution
Sloan Digital Sky Survey (SDSS) SkyServer
Database Performance
Schema Adaptation
Performance Benchmarking
Historical Data Analysis
Indexing
Vertical Partitioning
Embedding
PostgreSQL
Document Type Storage
SQL (Llenguatge de programació)
Sistemes incrustats (Informàtica)
Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació::Bases de dades
Descrição
Resumo:This study performs a dynamic cost-benefit analysis of migrating the Sloan Digital Sky Survey (SDSS) SkyServer database to optimized SQL and NoSQL schemas based on its workload evolution. Utilizing data spanning over two decades, the research explores the adaptation of database schemas at three pivotal historical points—2003, 2013, and 2023. Each phase is analyzed and optimized in both SQL and NoSQL frameworks to evaluate and compare the performance benefits. The project highlights the necessity for continual schema adjustments driven by evolving workloads and assesses the comparative effectiveness of SQL versus NoSQL solutions in optimizing database operations.

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