Authors: David Lengweiler, Marco Vogt, Heiko Schuldt

Multi-model database systems have gained increasing popularity due to their efficient management of diverse types of data and support for complex queries. They offer a unified approach for managing data in various formats, including structured, semi-structured, and unstructured data. However, benchmarking the performance of such systems is a challenging task, given their complexity, mainly due to their support for multiple data models. While significant research exists for benchmarking single-model databases, a comprehensive approach for evaluating multi-model databases is still in an early stage. To address this challenge, we propose MMSBench-Net, a benchmark for evaluating multi-model database systems that support structured relational, semi-structured document, and graph data models. MMSBench-Net enables comparative analysis of database systems and demonstrates how different workloads can reveal the strengths and weaknesses of multi-model database systems.
To demonstrate the effectiveness of the benchmark, we compare the performance of two database systems: Polypheny and SurrealDB. Our work is a first step towards a comprehensive evaluation methodology for multi-model database systems.


Link: Paper