Blockchain benchmarking framework

Enabling users to deploy, monitor, analyse and compare the behaviour of many different blockchain networks.

The Challenges

Comparing and evaluating the performance of different blockchain implementations.

Understanding their behavior, in the presence of faults or malicious attacks.

Setting up and configuring private deployments of blockchain protocols is complex, and time consuming.

Stress testing the protocols under “close-to-real” conditions is complex.

The Facts

The current blockchain ecosystem is fragmented.

Different implementations of heterogeneous blockchains.

The deployment processes of blockchain protocols:

have many dependencies and assume a certain level of technical expertise.

are complex and time-consuming.

are based on primitive command line deployment /testing scripts.

The Need

Αn open-source, easy to use, holistic, and extendable framework.

A framework that will incorporate technical and non-technical teams.

A framework to deploy, monitor, analyze, compare, and report various blockchain performance activities.

The Solution

A modular framework that aims to:

Automate the deployment processes of various blockchain protocols.

Abstracting the technical details from the end-user.

Analyze, and evaluate the behavior of various consensus proposals under different blockchain network deployments.

Expose the user to a UI, abstracting the complexities and time-consuming configuration processes from the end user.

Supported Networks

Supported Consensus

  • Proof of Work (PoW)
  • Proof of Stake (PoS)
  • XRP Ledger Consensus Protocol
  • Stellar Consensus Protocol
  • Clique


“Validating the Blockchain Benchmarking Framework through Controlled Deployments of XRPL and Ethereum”, IEEE Access (2024), M. Touloupou et al.

“A Systematic Literature Review Towards a Blockchain Benchmarking Framework.” IEEE Access (2022), M. Touloupou et al.

“Benchmarking Blockchains: The case of XRP Ledger and Beyond.” In Proceedings of the 55th Hawaii International Conference on System Sciences. 2022, M. Touloupou et al.

“Towards a Framework for Understanding the Performance of Blockchains”, BRAINS 2021 Conference, M. Touloupou et al.

Christodoulou, Klitos, Elias Iosif, Antonios Inglezakis, and Marinos Themistocleous. “Consensus crash testing: Exploring ripple’s decentralization degree in adversarial environments.” Future Internet 12, no. 3 (2020): 53.

Medium Article: “The Big Bang of Blockchain Consensus Algorithms: The Case of the XRP Ledger”, K. Christodoulou et al.

Medium Article: “The Big Bang of Blockchain Consensus Algorithms (Part II)”, M. Touloupou et al.

Medium Article: “The Big Bang of Blockchain Consensus Algorithms (Part III)”, M. Touloupou et al.