JetScope: Reliable and Interactive Analytics at Cloud Scale
Summary: JetScope: cloud-scale interactive analytics with a SQL-like declarative language for scalable, low-latency queries. Fine-grained fault tolerance with fast recovery that minimizes latency; optimized access methods and scheduling for deployments. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Eric Boutin (Microsoft)
- 2. Paul Brett (Microsoft)
- 3. Xiaoyu Chen (Microsoft)
- 4. Jaliya Ekanayake (Microsoft)
- 5. Tao Guan (Microsoft)
- 6. Anna Korsun (Microsoft)
- 7. Zhicheng Yin (Microsoft)
- 8. Nan Zhang (Microsoft)
- 9. Jingren Zhou (Microsoft)
BibTeX Citation
@article{boutin_vldb15,
title = {{JetScope: Reliable and Interactive Analytics at Cloud Scale}},
author = {Boutin, Eric and Brett, Paul and Chen, Xiaoyu and Ekanayake, Jaliya and Guan, Tao and Korsun, Anna and Yin, Zhicheng and Zhang, Nan and Zhou, Jingren},
journal = {PVLDB},
series = {{VLDB} '15},
volume = {8},
number = {12},
pages = {1680--1691},
doi = {10.14778/2824032.2824064},
url = {https://doi.org/10.14778/2824032.2824064},
year = {2015}
}
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,681 | Survivability of Cloud Databases - Factors and Prediction | 2018 | SIGMOD | 6.1237253e-05 |
| 6,946 | KEA: Tuning an Exabyte-Scale Data Infrastructure | 2021 | SIGMOD | 5.7309848e-05 |
| 7,182 | Bubble Execution: Resource-aware Reliable Analytics at Cloud Scale | 2018 | VLDB | 5.6793679e-05 |
| 7,762 | Runtime Variation in Big Data Analytics | 2023 | SIGMOD | 5.5501898e-05 |
| 11,685 | Toto - Benchmarking the Efficiency of a Cloud Service | 2021 | SIGMOD | 5.093636e-05 |
| 11,728 | Fangorn: Adaptive Execution Framework for Heterogeneous Workloads on Shared Clusters | 2021 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 11 of 11 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6 | Pig Latin: A Not-So-Foreign Language for Data Processing | 2008 | SIGMOD | 0.0010686205 |
| 24 | Spark SQL: Relational Data Processing in Spark | 2015 | SIGMOD | 0.00054865648 |
| 32 | Hive - A Warehousing Solution Over a Map-Reduce Framework | 2009 | VLDB | 0.00050111008 |
| 49 | Weaving Relations for Cache Performance | 2001 | VLDB | 0.00043781096 |
| 51 | Dremel: Interactive Analysis of Web-Scale Datasets | 2010 | VLDB | 0.0004291425 |
| 330 | Impala: A Modern, Open-Source SQL Engine for Hadoop | 2015 | CIDR | 0.0002104801 |
| 425 | Shark: SQL and Rich Analytics at Scale | 2013 | SIGMOD | 0.00018704491 |
| 607 | F1: A Distributed SQL Database That Scales | 2013 | VLDB | 0.00015800238 |
| 1,054 | Interactive Analytical Processing in Big Data Systems: A Cross-Industry Study of MapReduce Workloads | 2012 | VLDB | 0.00012390673 |
| 1,352 | Scuba: Diving into Data at Facebook | 2013 | VLDB | 0.00011064595 |
| 1,889 | SQL-on-Hadoop: Full Circle Back to Shared-Nothing Database Architectures | 2014 | VLDB | 9.5335988e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 6,208 | The CloudMdsQL Multistore System | 2016 | SIGMOD |
| 2 | 9,640 | Supporting Scalable Analytics with Latency Constraints | 2015 | VLDB |
| 3 | 1,969 | PIQL: Success-Tolerant Query Processing in the Cloud | 2012 | VLDB |
| 4 | 7,098 | QueryScope: Visualizing Queries for Repeatable Database Tuning | 2008 | VLDB |
| 5 | 7,617 | Squall: Scalable Real-time Analytics | 2016 | VLDB |
| 6 | 939 | Starling: A Scalable Query Engine on Cloud Functions | 2020 | SIGMOD |
| 7 | 3,578 | Advanced Join Strategies for Large-Scale Distributed Computation | 2014 | VLDB |
| 8 | 30 | SCOPE: Easy and Efficient Parallel Processing of Massive Data Sets | 2008 | VLDB |
| 9 | 4,742 | Continuous Cloud-Scale Query Optimization and Processing | 2013 | VLDB |
| 10 | 7,182 | Bubble Execution: Resource-aware Reliable Analytics at Cloud Scale | 2018 | VLDB |