Benchmarking Data Management Systems for Microservices
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866916251808301056 |
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| author | Laigner, Rodrigo Zhou, Yongluan |
| author_facet | Laigner, Rodrigo Zhou, Yongluan |
| contents | Microservice architectures are a popular choice for deploying large-scale data-intensive applications. This architectural style allows microservice practitioners to achieve requirements related to loose coupling, fault contention, workload isolation, higher data availability, scalability, and independent schema evolution.
Although the industry has been employing microservices for over a decade, existing microservice benchmarks lack essential data management challenges observed in practice, including distributed transaction processing, consistent data querying and replication, event processing, and data integrity constraint enforcement. This gap jeopardizes the development of novel data systems that embrace the complex nature of data-intensive microservices. In this talk, we share our experience in designing Online Marketplace, a novel benchmark that embraces core data management requirements intrinsic to real-world microservices.
By implementing the benchmark in state-of-the-art data platforms, we experience the pain practitioners face in assembling several heterogeneous components to realize their requirements. Our evaluation demonstrates Online Marketplace allows experimenting key properties sought by microservice practitioners, thus fomenting the design of novel data management systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_11529 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Benchmarking Data Management Systems for Microservices Laigner, Rodrigo Zhou, Yongluan Databases Software Engineering Microservice architectures are a popular choice for deploying large-scale data-intensive applications. This architectural style allows microservice practitioners to achieve requirements related to loose coupling, fault contention, workload isolation, higher data availability, scalability, and independent schema evolution. Although the industry has been employing microservices for over a decade, existing microservice benchmarks lack essential data management challenges observed in practice, including distributed transaction processing, consistent data querying and replication, event processing, and data integrity constraint enforcement. This gap jeopardizes the development of novel data systems that embrace the complex nature of data-intensive microservices. In this talk, we share our experience in designing Online Marketplace, a novel benchmark that embraces core data management requirements intrinsic to real-world microservices. By implementing the benchmark in state-of-the-art data platforms, we experience the pain practitioners face in assembling several heterogeneous components to realize their requirements. Our evaluation demonstrates Online Marketplace allows experimenting key properties sought by microservice practitioners, thus fomenting the design of novel data management systems. |
| title | Benchmarking Data Management Systems for Microservices |
| topic | Databases Software Engineering |
| url | https://arxiv.org/abs/2405.11529 |