Cloud Analytics Benchmark
van Renen A, Leis V (2023)
Publication Type: Journal article
Publication year: 2023
Journal
Book Volume: 16
Pages Range: 1413-1425
Journal Issue: 6
Abstract
The cloud facilitates the transition to a service-oriented perspective. This affects cloud-native data management in general, and data analytics in particular. Instead of managing a multi-node database cluster on-premise, end users simply send queries to a managed cloud data warehouse and receive results. While this is obviously very attractive for end users, database system architects still have to engineer systems for this new service model. There are currently many competing architectures ranging from self-hosted (Presto, PostgreSQL), over managed (Snowflake, Amazon Redshift) to query-as-a-service (Amazon Athena, Google BigQuery) offerings. Benchmarking these architectural approaches is currently difficult, and it is not even clear what the metrics for a comparison should be. To overcome these challenges, we first analyze a real-world query trace from Snowflake and compare its properties to that of TPC-H and TPC-DS. Doing so, we identify important differences that distinguish traditional benchmarks from real-world cloud data warehouse workloads. Based on this analysis, we propose the Cloud Analytics Benchmark (CAB). By incorporating workload fluctuations and multi-tenancy, CAB allows evaluating different designs in terms of user-centered metrics such as cost and performance.
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Germany (DE)How to cite
APA:
van Renen, A., & Leis, V. (2023). Cloud Analytics Benchmark. Proceedings of the VLDB Endowment, 16(6), 1413-1425. https://dx.doi.org/10.14778/3583140.3583156
MLA:
van Renen, Alexander, and Viktor Leis. "Cloud Analytics Benchmark." Proceedings of the VLDB Endowment 16.6 (2023): 1413-1425.
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