PolyBench: The First Benchmark for Polystores

Jeyhun Karimov, Tilmann Rabl, Volker Markl

In: Performance Evaluation and Benchmarking for the Era of Artificial Intelligence - 10th TPC Technology Conference. Technology Conference on Performance Evaluation and Benchmarking (TPCTC-2018) August 27-31 Rio de Janeiro Brazil Seiten 24-41 Lecture Notes in Computer Science (LNCS) 11135 Spinger 2018.


Modern business intelligence requires data processing not only across a huge variety of domains but also across different paradigms, such as relational, stream, and graph models. This variety is a challenge for existing systems that typically only support a single or few different data models. Polystores were proposed as a solution for this challenge and received wide attention both in academia and in industry. These are systems that integrate different specialized data processing engines to enable fast processing of a large variety of data models. Yet, there is no standard to assess the performance of polystores. The goal of this work is to develop the first benchmark for polystores. To capture the flexibility of polystores, we focus on high level features in order to enable an execution of our benchmark suite on a large set of polystore solutions.


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Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence