# Enabling Cross-Language Data Integration and Scalable Analytics in Decentralized Finance

arXiv: https://arxiv.org/abs/2311.02272 · HTML: https://mlsanity.com/paper/2311.02272/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Nov 2023.

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

- [From Risk to Rescue: An Agentic Survival Analysis Framework for Liquidation Prevention](https://mlsanity.com/paper/2604.14583/) (2026)

## Abstract (arXiv)

With the agile development process of most academic and corporate entities, designing a robust computational back-end system that can support their ever-changing data needs is a constantly evolving challenge. We propose the implementation of a data and language-agnostic system design that handles different data schemes and sources while subsequently providing researchers and developers a way to connect to it that is supported by a vast majority of programming languages. To validate the efficacy of a system with this proposed architecture, we integrate various data sources throughout the decentralized finance (DeFi) space, specifically from DeFi lending protocols, retrieving tens of millions of data points to perform analytics through this system. We then access and process the retrieved data through several different programming languages (R-Lang, Python, and Java). Finally, we analyze the performance of the proposed architecture in relation to other high-performance systems and explore how this system performs under a high computational load.