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: 7576
Venue: SIGMOD
Year: 2026
Pagerank: 5.093636e-05
Overall Rank: 10,368 | 28.87%
DOI: 10.1145/3769790

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

1. Lasantha Fernando (University of Waterloo)
2. Taebin Kim (University of Waterloo)
3. Khuzaima Daudjee (University of Waterloo)
4. Tilmann Rabl (Hasso Plattner Institute; University of Potsdam)

BibTeX Citation

@inproceedings{fernando_sigmod26,
        title = {{Enjima: A Resource-Adaptive Stream Processing System}},
        author = {Fernando, Lasantha and Kim, Taebin and Daudjee, Khuzaima and Rabl, Tilmann},
        series = {{SIGMOD} '26},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3769790},
        url = {https://dl.acm.org/doi/10.1145/3769790},
        year = {2026}
}

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
127	The Design of the Borealis Stream Processing Engine	2005	CIDR	0.00030738755
361	The Dataflow Model: A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-Scale, Unbounded, Out-of-Order Data Processing	2015	VLDB	0.00020138717
587	Linear Road: A Stream Data Management Benchmark	2004	VLDB	0.00016106078
1,027	Chain: Operator Scheduling for Memory Minimization in Data Stream Systems	2003	SIGMOD	0.00012563656
1,190	Structured Streaming: A Declarative API for Real-Time Applications in Apache Spark	2018	SIGMOD	0.00011743246
2,447	Operator Scheduling in a Data Stream Manager	2003	VLDB	8.5728111e-05
3,060	SABER: Window-Based Hybrid Stream Processing for Heterogeneous Architectures	2016	SIGMOD	7.8062155e-05
3,851	Analyzing Efficient Stream Processing on Modern Hardware	2019	VLDB	7.0735328e-05
4,820	LightSaber: Efficient Window Aggregation on Multi-core Processors	2020	SIGMOD	6.493623e-05
5,206	BriskStream: Scaling Data Stream Processing on Shared-Memory Multicore Architectures	2019	SIGMOD	6.3180444e-05
7,814	Rethinking Stateful Stream Processing with RDMA	2022	SIGMOD	5.5389009e-05
8,679	Efficient Scheduling of Heterogeneous Continuous Queries	2006	VLDB	5.3862828e-05
8,720	Robust Real-time Query Processing with QStream	2005	VLDB	5.3774243e-05
8,820	Real Time Analytics: Algorithms and Systems	2015	VLDB	5.3625678e-05
11,665	Klink: Progress-Aware Scheduling for Streaming Data Systems	2021	SIGMOD	5.093636e-05

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