How Reliable Are Streams? End-to-End Processing-Guarantee Validation and Performance Benchmarking of Stream Processing Systems
Summary: PGVal: first end-to-end tool to empirically validate stream processing guarantees, introducing metrics (reliability, reliable throughput, failure cost) and a refined latency definition. Benchmarks Kafka Streams, Storm, Flink under varied rates, partitions, topologies, parallelism and injected faults, showing guarantees often break across realistic changes and providing a failure model and mitigation guidance. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Jawad Tahir
- 2. Ruben Mayer
- 3. Christoph Doblander
- 4. Hans-Arno Jacobsen
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 288 | Storm @Twitter | 2014 | SIGMOD | 0.00028939871 |
| 538 | The Dataflow Model: A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-Scale, Unbounded, Out-of-Order Data Processing | 2015 | VLDB | 0.00020678804 |
| 600 | Linear Road: A Stream Data Management Benchmark | 2004 | VLDB | 0.0001938744 |
| 7,930 | Demonstrating PDSP-Bench: A Benchmarking System for Parallel and Distributed Stream Processing | 2025 | SIGMOD | 4.613363e-05 |
| 7,938 | Correctness in Stream Processing: Challenges and Opportunities | 2022 | CIDR | 4.613363e-05 |
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