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SABER: Window-Based Hybrid Stream Processing for Heterogeneous Architectures
Summary: SABER is a window-based streaming engine for CPUs and GPUs, enabling data-parallel streaming SQL. Adaptive lookahead scheduling maps work to the device; pipelined CPU-GPU transfers hide movement, boosting throughput with low latency across windows.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 5097
- Venue
- SIGMOD
- Year
- 2016
- Pagerank
- 6.7804471e-05
- Overall Rank
- 3,762 | 73.83%
- DOI
-
10.1145/2882903.2882906
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 21 of 21 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 3,327 |
Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects |
2020 |
SIGMOD |
7.2205738e-05 |
| 4,488 |
Analyzing Efficient Stream Processing on Modern Hardware |
2019 |
VLDB |
6.145117e-05 |
| 5,193 |
LightSaber: Efficient Window Aggregation on Multi-core Processors |
2020 |
SIGMOD |
5.6371049e-05 |
| 5,657 |
BriskStream: Scaling Data Stream Processing on Shared-Memory Multicore Architectures |
2019 |
SIGMOD |
5.3864606e-05 |
| 6,476 |
Parallel Index-based Stream Join on a Multicore CPU |
2020 |
SIGMOD |
5.0496617e-05 |
| 6,629 |
A Holistic View of Stream Partitioning Costs |
2017 |
VLDB |
4.9880986e-05 |
| 6,648 |
Grizzly: Efficient Stream Processing Through Adaptive Query Compilation |
2020 |
SIGMOD |
4.9771723e-05 |
| 6,721 |
Beyond Analytics: The Evolution of Stream Processing Systems |
2020 |
SIGMOD |
4.9492015e-05 |
| 8,001 |
Rethinking Stateful Stream Processing with RDMA |
2022 |
SIGMOD |
4.6092573e-05 |
| 8,922 |
Enabling Signal Processing over Data Streams |
2017 |
SIGMOD |
4.427232e-05 |
| 9,083 |
AT-GIS: Highly Parallel Spatial Query Processing with Associative Transducers |
2016 |
SIGMOD |
4.399861e-05 |
| 9,496 |
Scabbard: Single-Node Fault-Tolerant Stream Processing |
2022 |
VLDB |
4.3341665e-05 |
| 9,733 |
ContTune: Continuous Tuning by Conservative Bayesian Optimization for Distributed Stream Data Processing Systems |
2023 |
VLDB |
4.2942813e-05 |
| 9,797 |
Dalton: Learned Partitioning for Distributed Data Streams |
2023 |
VLDB |
4.2818172e-05 |
| 9,926 |
Darwin: Scale-In Stream Processing |
2022 |
CIDR |
4.2543961e-05 |
| 10,077 |
Enjima: A Resource-Adaptive Stream Processing System |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,290 |
RayDB: Building Databases with Ray Tracing Cores |
2026 |
VLDB |
4.1945683e-05 |
| 10,405 |
Flux: Unifying Heterogeneous Infrastructure for Alibaba AnalyticDB |
2025 |
SIGMOD |
4.1945683e-05 |
| 10,674 |
Improving Time Series Data Compression in Apache IoTDB |
2025 |
VLDB |
4.1945683e-05 |
| 10,714 |
Towards Designing Future-Proof Data Processing Systems |
2025 |
VLDB |
4.1945683e-05 |
| 11,468 |
Klink: Progress-Aware Scheduling for Streaming Data Systems |
2021 |
SIGMOD |
4.1945683e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 20 of 20 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 41 |
NiagaraCQ: A Scalable Continuous Query System for Internet Databases |
2000 |
SIGMOD |
0.00073964959 |
| 239 |
GPUTeraSort: High Performance Graphics Co-processor Sorting for Large Database Management |
2006 |
SIGMOD |
0.00031617428 |
| 288 |
Storm @Twitter |
2014 |
SIGMOD |
0.00028939871 |
| 314 |
MillWheel: Fault-Tolerant Stream Processing at Internet Scale |
2013 |
VLDB |
0.00028084774 |
| 591 |
TelegraphCQ: Continuous Dataflow Processing |
2003 |
SIGMOD |
0.00019569071 |
| 600 |
Linear Road: A Stream Data Management Benchmark |
2004 |
VLDB |
0.0001938744 |
| 1,098 |
Trill: A High-Performance Incremental Query Processor for Diverse Analytics |
2015 |
VLDB |
0.00014114442 |
| 1,226 |
Integrating Scale Out and Fault Tolerance in Stream Processing using Operator State Management |
2013 |
SIGMOD |
0.00013180799 |
| 1,273 |
The Yin and Yang of Processing Data Warehousing Queries on GPU Devices |
2013 |
VLDB |
0.00012912938 |
| 1,287 |
Hardware-Oblivious Parallelism for In-Memory Column-Stores |
2013 |
VLDB |
0.00012820443 |
| 1,694 |
How Soccer Players Would do Stream Joins |
2011 |
SIGMOD |
0.00010893764 |
| 2,519 |
Revisiting Co-Processing for Hash Joins on the Coupled CPU-GPU Architecture |
2013 |
VLDB |
8.6078505e-05 |
| 2,879 |
Microsoft CEP Server and Online Behavioral Targeting |
2009 |
VLDB |
7.9695819e-05 |
| 3,378 |
General Incremental Sliding-Window Aggregation |
2015 |
VLDB |
7.1622572e-05 |
| 3,569 |
S-Store: A Streaming NewSQL System for Big Velocity Applications |
2014 |
VLDB |
6.9608969e-05 |
| 3,696 |
Why it is time for a HyPE: A Hybrid Query Processing Engine for Efficient GPU Coprocessing in DBMS |
2013 |
VLDB |
6.834483e-05 |
| 4,085 |
In-Cache Query Co-Processing on Coupled CPU-GPU Architectures |
2015 |
VLDB |
6.4620277e-05 |
| 6,071 |
IBM InfoSphere Streams for Scalable, Real-Time, Intelligent Transportation Services |
2010 |
SIGMOD |
5.2261393e-05 |
| 6,646 |
Geospatial Stream Query Processing using Microsoft SQL Server StreamInsight |
2010 |
VLDB |
4.9772435e-05 |
| 7,038 |
Demonstrating Efficient Query Processing in Heterogeneous Environments |
2014 |
SIGMOD |
4.8546906e-05 |
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| 2,763 |
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2020 |
SIGMOD |
5.6371049e-05 |