TY - GEN
T1 - Performance Comparison of Operations in the File System and in Embedded Key-Value Databases
AU - Hines, Jesse
AU - Cunningham, Nicholas
AU - Alférez, Germán H.
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023
Y1 - 2023
N2 - A common scenario when developing local PC applications such as games, mobile apps, or presentation software is storing many small files or records as application data and needing to retrieve and manipulate those records with some unique ID. In this kind of scenario, a developer has the choice of simply saving the records as files with their unique ID as the filename or using an embedded on-disk key-value database. Many file systems have performance issues when handling large number of small files, but developers may want to avoid a dependency on an embedded database if it offers little benefit or has a detrimental effect on performance for their use case. Despite the need for benchmarks to enable informed answers to this design decision, little research has been done in this area. Our contribution is the comparison and analysis of the performance for the insert, update, get, and remove operations and the space efficiency of storing records as files vs. using key-value embedded databases including SQLite3, LevelDB, RocksDB, and Berkeley DB.
AB - A common scenario when developing local PC applications such as games, mobile apps, or presentation software is storing many small files or records as application data and needing to retrieve and manipulate those records with some unique ID. In this kind of scenario, a developer has the choice of simply saving the records as files with their unique ID as the filename or using an embedded on-disk key-value database. Many file systems have performance issues when handling large number of small files, but developers may want to avoid a dependency on an embedded database if it offers little benefit or has a detrimental effect on performance for their use case. Despite the need for benchmarks to enable informed answers to this design decision, little research has been done in this area. Our contribution is the comparison and analysis of the performance for the insert, update, get, and remove operations and the space efficiency of storing records as files vs. using key-value embedded databases including SQLite3, LevelDB, RocksDB, and Berkeley DB.
KW - Database Performances
KW - Databases
KW - File Systems
UR - https://www.scopus.com/pages/publications/85172284112
U2 - 10.1007/978-3-031-37963-5_27
DO - 10.1007/978-3-031-37963-5_27
M3 - Conference contribution
AN - SCOPUS:85172284112
SN - 9783031379628
T3 - Lecture Notes in Networks and Systems
SP - 386
EP - 400
BT - Intelligent Computing - Proceedings of the 2023 Computing Conference
A2 - Arai, Kohei
PB - Springer Science and Business Media Deutschland GmbH
T2 - Proceedings of the Computing Conference 2023
Y2 - 22 June 2023 through 23 June 2023
ER -