# Reproducible Experiments for Comparing Apache Flink and Apache Spark on Public Clouds

arXiv: https://arxiv.org/abs/1610.04493 · HTML: https://mlsanity.com/paper/1610.04493/

## Key facts

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

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

- [Reproducible and Portable Big Data Analytics in the Cloud](https://mlsanity.com/paper/2112.09762/) (2021)

## Abstract (arXiv)

Big data processing is a hot topic in today's computer science world. There is a significant demand for analysing big data to satisfy many requirements of many industries. Emergence of the Kappa architecture created a strong requirement for a highly capable and efficient data processing engine. Therefore data processing engines such as Apache Flink and Apache Spark emerged in open source world to fulfil that efficient and high performing data processing requirement. There are many available benchmarks to evaluate those two data processing engines. But complex deployment patterns and dependencies make those benchmarks very difficult to reproduce by our own. This project has two main goals. They are making few of community accepted benchmarks easily reproducible on cloud and validate the performance claimed by those studies.