# A Survey on the Evolution of Stream Processing Systems

arXiv: https://arxiv.org/abs/2008.00842 · HTML: https://mlsanity.com/paper/2008.00842/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Aug 2020.

## Built on by (most cited first, 5 of 5)

- [Stream-Based Monitoring of Algorithmic Fairness](https://mlsanity.com/paper/2501.18331/) (2025)
- [Engineering Reliable Coding Agents: Evaluating and Operating the System Around the Model](https://mlsanity.com/paper/2608.13867/) (2026)
- [AutoStreamPipe: LLM Assisted Automatic Generation of Data Stream Processing Pipelines](https://mlsanity.com/paper/2510.23408/) (2025)
- [Benchmarking of CPU-intensive Stream Data Processing in The Edge Computing Systems](https://mlsanity.com/paper/2505.07755/) (2025)
- [Can Large Language Models Reason about Event-Time Stream-Processing Semantics?](https://mlsanity.com/paper/2608.12348/) (2026)

## Abstract (arXiv)

Stream processing has been an active research field for more than 20 years, but it is now witnessing its prime time due to recent successful efforts by the research community and numerous worldwide open-source communities. This survey provides a comprehensive overview of fundamental aspects of stream processing systems and their evolution in the functional areas of out-of-order data management, state management, fault tolerance, high availability, load management, elasticity, and reconfiguration. We review noteworthy past research findings, outline the similarities and differences between early ('00-'10) and modern ('11-'22) streaming systems, and discuss recent trends and open problems.