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Darwin: Scale-In Stream Processing
Summary: Propose “scale-in”: compile-tailored stream processing that maximizes utilization of existing single- and multi-node hardware and supports recoverable larger-than-memory state, avoiding the scale-up vs availability tradeoff. Darwin prototype implements this and reports ~10× speedups vs scale-out systems while matching scale-up throughput.
(summarized by gpt-5-mini on Feb 09 2026)
- Paper ID
- 450
- Venue
- CIDR
- Year
- 2022
- Pagerank
- 4.2543961e-05
- Overall Rank
- 9,926 | 30.95%
- DOI
-
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Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 60 |
Efficiently Compiling Efficient Query Plans for Modern Hardware |
2011 |
VLDB |
0.00064439773 |
| 899 |
Faster: A Concurrent Key-Value Store with In-Place Updates |
2018 |
SIGMOD |
0.00015509287 |
| 1,098 |
Trill: A High-Performance Incremental Query Processor for Diverse Analytics |
2015 |
VLDB |
0.00014114442 |
| 3,085 |
Viper: An Efficient Hybrid PMem-DRAM Key-Value Store |
2021 |
VLDB |
7.5993418e-05 |
| 3,762 |
SABER: Window-Based Hybrid Stream Processing for Heterogeneous Architectures |
2016 |
SIGMOD |
6.7804471e-05 |
| 4,281 |
Maximizing Persistent Memory Bandwidth Utilization for OLAP Workloads |
2021 |
SIGMOD |
6.2940039e-05 |
| 4,483 |
DFI: The Data Flow Interface for High-Speed Networks |
2021 |
SIGMOD |
6.148188e-05 |
| 4,488 |
Analyzing Efficient Stream Processing on Modern Hardware |
2019 |
VLDB |
6.145117e-05 |
| 5,448 |
Enabling Low Tail Latency on Multicore Key-Value Stores |
2020 |
VLDB |
5.501371e-05 |
| 5,657 |
BriskStream: Scaling Data Stream Processing on Shared-Memory Multicore Architectures |
2019 |
SIGMOD |
5.3864606e-05 |
| 6,221 |
Charting the Design Space of Query Execution using VOILA |
2021 |
VLDB |
5.1512158e-05 |
| 6,648 |
Grizzly: Efficient Stream Processing Through Adaptive Query Compilation |
2020 |
SIGMOD |
4.9771723e-05 |
| 7,373 |
Hazelcast Jet: Low-latency Stream Processing at the 99.99th Percentile |
2021 |
VLDB |
4.7494183e-05 |
Semantically Similar Papers
| Overall Rank |
Paper |
Year |
Venue |
Pagerank |
| 1,548 |
Structured Streaming: A Declarative API for Real-Time Applications in Apache Spark |
2018 |
SIGMOD |
0.00011431383 |
| 5,045 |
Massive Scale-out of Expensive Continuous Queries |
2011 |
VLDB |
5.740793e-05 |
| 6,648 |
Grizzly: Efficient Stream Processing Through Adaptive Query Compilation |
2020 |
SIGMOD |
4.9771723e-05 |
| 7,660 |
Scalable Delivery of Stream Query Result |
2009 |
VLDB |
4.6862657e-05 |
| 10,043 |
Accelerating Stream Processing Engines via Hardware Offloading |
2026 |
SIGMOD |
4.1945683e-05 |
| 2,772 |
Quickstep: A Data Platform Based on the Scaling-Up Approach |
2018 |
VLDB |
8.1401661e-05 |
| 11,468 |
Klink: Progress-Aware Scheduling for Streaming Data Systems |
2021 |
SIGMOD |
4.1945683e-05 |
| 4,795 |
Rhino: Efficient Management of Very Large Distributed State for Stream Processing Engines |
2020 |
SIGMOD |
5.9158043e-05 |
| 1,226 |
Integrating Scale Out and Fault Tolerance in Stream Processing using Operator State Management |
2013 |
SIGMOD |
0.00013180799 |
| 4,488 |
Analyzing Efficient Stream Processing on Modern Hardware |
2019 |
VLDB |
6.145117e-05 |