Date of Award
5-2025
Culminating Project Type
Starred Paper
Styleguide
ieee
Degree Name
Computer Science: M.S.
Department
Computer Science and Information Technology
College
School of Science and Engineering
First Advisor
Dr. Adriano Cavalcanti
Second Advisor
Dr. Jie Hu Meichsner
Third Advisor
Dr. Jalal Khalil
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Keywords and Subject Headings
Database SurrealDB SurrealQL
Abstract
This thesis presents a comprehensive study of query optimization strategies in SurrealDB, a multi-model database system. Through systematic analysis of various query patterns and data structures, we investigate the performance characteristics of SurrealDB’s features, including edge traversals, record links, indexing methods, and filtering operations. Our research reveals the significant impact of record size on query performance, with smaller records consistently outperforming larger ones due to RocksDB’s underlying mechanics. We demonstrate that edge traversals, particularly when utilizing record IDs as intermediates, often yield performance gains, though this benefit diminishes with larger result sets. Record links emerge as an efficient alternative to edges for certain relationship queries, albeit with limitations in bidirectional navigation scenarios. Our findings highlight unexpected performance disparities between the CONTAINS and IN keywords in indexed contexts, emphasizing the critical role of proper indexing in query optimization. We also explore the performance implications of scope variables, fetch operations, and various filtering techniques. The study reveals that optimal query strategies often depend on the interplay between record size, query scope, and overall execution time. These insights provide valuable guidance for database designers and developers in crafting efficient queries and data models in SurrealDB, while also identifying areas for potential further optimization in the database engine.
Recommended Citation
pederson, michael, "Query Optimization in SurrealDB" (2025). Culminating Projects in Computer Science and Information Technology. 60.
https://repository.stcloudstate.edu/csit_etds/60
