# On measuring performances of C-SPARQL and CQELS

arXiv: https://arxiv.org/abs/1611.08269 · HTML: https://mlsanity.com/paper/1611.08269/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Nov 2016.

## Built on by (most cited first, 1 of 1)

- [Deep Neural Networks for Approximating Stream Reasoning with C-SPARQL](https://mlsanity.com/paper/2106.08452/) (2021)

## Abstract (arXiv)

To cope with the massive growth of semantic data streams, several RDF Stream Processing (RSP) engines have been implemented. The efficiency of their throughput, latency and memory consumption can be evaluated using available benchmarks such as LSBench and City- Bench. Nevertheless, these benchmarks lack an in-depth performance evaluation as some measurement metrics have not been considered. The main goal of this paper is to analyze the performance of two popular RSP engines, namely C-SPARQL and CQELS, when varying a set of performance metrics. More precisely, we evaluate the impact of stream rate, number of streams and window size on execution time as well as on memory consumption.