  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.
