Fast Queries Over Heterogeneous Data Through Engine Customization
Summary: Proteus natively supports CSV, JSON, and relational binary data via a multi-format algebra. It uses per-query code generation to tailor storage and execution to the dataset and workload, delivering fast cross-format analytics under one interface. (summarized by gpt-5-nano on Feb 09 2026)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,305 | Robust Query Processing in Co-Processor-accelerated Databases | 2016 | SIGMOD | 7.2460965e-05 |
| 3,170 | Quality-driven Integration of Heterogeneous Information Systems | 1999 | VLDB | 7.4482367e-05 |
| 6,407 | Just-In-Time Data Virtualization: Lightweight Data Management with ViDa | 2015 | CIDR | 5.076547e-05 |
| 5,301 | ReCache: Reactive Caching for Fast Analytics over Heterogeneous Data | 2018 | VLDB | 5.5790928e-05 |
| 9,028 | Enabling Rich Queries Over Heterogeneous Data From Diverse Sources In HealthCare | 2020 | CIDR | 4.4043898e-05 |
| 9,857 | Towards Unifying Query Interpretation and Compilation | 2023 | CIDR | 4.269353e-05 |
| 8,861 | A Model for Query Execution Over Heterogeneous Instances | 2024 | CIDR | 4.4331977e-05 |
| 6,803 | Proteus: Autonomous Adaptive Storage for Mixed Workloads | 2022 | SIGMOD | 4.9224958e-05 |
| 3,548 | Adaptive Query Processing on RAW Data | 2014 | VLDB | 6.9859242e-05 |
| 8,118 | Maximus: A Modular Accelerated Query Engine for Data Analytics on Heterogeneous Systems | 2025 | SIGMOD | 4.5814829e-05 |