DataPlat 2023, MongoDB Data Versioning Performance: local versus Atlas

MongoDB Data Versioning Performance: local versus Atlas

Lucia de Espona, Ela Pustulka

School of Business, University of Applied Sciences and Arts Northwestern Switzerland FHNW, Riggenbachstrasse 16, 4600 Olten, Switzerland

Abstract

We focus on versioning for NoSQL data on MongoDB. Versioning is essential for security audits, legal compliance and business strategy development. For each type of business object, we maintain two collections and split the data into currently valid objects and the archive. We previously presented a versioning algorithm and a preliminary evaluation on a local database, with version write times of 4 to 13ms, and versioning queries in 2 to 4ms. Here, we introduce bulk operations and present a performance study measuring all versioning operations on MongoDB Atlas. Cloud experiments show that version writes take 14 to 60ms. Queries need between 14 and 25ms. Using bulk versioning is faster, as writes need between 3 and 10ms. Cloud times are slower than those seen in local tests but the performance penalty due to network latency, imposed by the use of Atlas, is mitigated by the newly added bulk operations. Overall, the experiments show that the performance is satisfactory for an enterprise resource planning (ERP) system for small and medium enterprises (SMEs).

Keywords

database, NoSQL, document versioning, CRUD, ERP, MongoDB, performance, bulk operations, cloud

DataPlat’23: 2nd International Workshop on Data Platform Design, Management, and Optimization, March 28, 2023, Ioannina, Greece