Year: 2024
Type: conference-paper
Abstract: As organizations increasingly adopt data-driven approaches, the demand for analyzing and processing massive datasets continues to rise. While traditional SQL-based systems are often used for transactional workloads, they face significant limitations when addressing analytical workloads. Analytical queries require optimizing for large-scale data traversal, complex aggregations, and ensuring performance over diverse data arrangements.
Authors: Pulkit Singhal, Sheldon Tauro
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4411624695