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Enjima: A Resource-Adaptive Stream Processing System
Summary: Enjima is a scale-up, stream-aware SPE using eager, cache-aligned block memory and variable batching to avoid allocation stalls and reduce memory accesses. A state-based scheduler exploits operator cost, selectivity and latency-gradient to adapt CPU/memory, achieving up to 6.3x throughput and ~1000x lower latency.
(summarized by gpt-5-mini on Feb 11 2026)
- Paper ID
- 7387
- Venue
- SIGMOD
- Year
- 2026
- Pagerank
- 4.1905499e-05
- Overall Rank
- 10,077 | 29.97%
- DOI
-
10.1145/3769790
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
Outgoing Citations (Sorted by Pagerank)
Showing 15 of 15 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 191 |
The Design of the Borealis Stream Processing Engine |
2005 |
CIDR |
0.00035714897 |
| 536 |
The Dataflow Model: A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-Scale, Unbounded, Out-of-Order Data Processing |
2015 |
VLDB |
0.00020651621 |
| 601 |
Linear Road: A Stream Data Management Benchmark |
2004 |
VLDB |
0.00019372971 |
| 1,136 |
Chain: Operator Scheduling for Memory Minimization in Data Stream Systems |
2003 |
SIGMOD |
0.00013745517 |
| 1,546 |
Structured Streaming: A Declarative API for Real-Time Applications in Apache Spark |
2018 |
SIGMOD |
0.00011418993 |
| 2,406 |
Operator Scheduling in a Data Stream Manager* |
2003 |
VLDB |
8.8718534e-05 |
| 3,771 |
SABER: Window-Based Hybrid Stream Processing for Heterogeneous Architectures |
2016 |
SIGMOD |
6.7738535e-05 |
| 4,490 |
Analyzing Efficient Stream Processing on Modern Hardware |
2019 |
VLDB |
6.137834e-05 |
| 5,357 |
LightSaber: Efficient Window Aggregation on Multi-core Processors |
2020 |
SIGMOD |
5.5512343e-05 |
| 5,670 |
BriskStream: Scaling Data Stream Processing on Shared-Memory Multicore Architectures |
2019 |
SIGMOD |
5.3799054e-05 |
| 8,004 |
Rethinking Stateful Stream Processing with RDMA |
2022 |
SIGMOD |
4.6048388e-05 |
| 8,678 |
Efficient Scheduling of Heterogeneous Continuous Queries |
2006 |
VLDB |
4.4644955e-05 |
| 8,721 |
Robust Real-time Query Processing with QStream |
2005 |
VLDB |
4.4558332e-05 |
| 8,815 |
Real Time Analytics: Algorithms and Systems |
2015 |
VLDB |
4.4395913e-05 |
| 11,471 |
Klink: Progress-Aware Scheduling for Streaming Data Systems |
2021 |
SIGMOD |
4.1905499e-05 |
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| Overall Rank |
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Year |
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Pagerank |
| 5,670 |
BriskStream: Scaling Data Stream Processing on Shared-Memory Multicore Architectures |
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VLDB |
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