The Easiest Way of Turning your Relational Database into a Blockchain -- and the Cost of Doing So

TL;DR

This paper demonstrates how to integrate relational databases with blockchain frameworks, specifically Tendermint Core, to enable deterministic SQL execution on a fully replicated database, analyzing the performance trade-offs involved.

Contribution

It introduces a method to combine relational DBMSs with blockchain frameworks, providing insights into integration challenges and performance implications.

Findings

Relational databases can be integrated into blockchain frameworks for deterministic SQL execution.

Blockchain layer introduces measurable throughput and latency overhead.

Recommendations for efficient deployment of relational blockchains are provided.

Abstract

Blockchain systems essentially consist of two levels: The network level has the responsibility of distributing an ordered stream of transactions to all nodes of the network in exactly the same way, even in the presence of a certain amount of malicious parties (byzantine fault tolerance). On the node level, each node then receives this ordered stream of transactions and executes it within some sort of transaction processing system, typically to alter some kind of state. This clear separation into two levels as well as drastically different application requirements have led to the materialization of the network level in form of so-called blockchain frameworks. While providing all the "blockchain features", these frameworks leave the node level backend flexible or even left to be implemented depending on the specific needs of the application. In the following paper, we present how to integrate a highly versatile transaction processing system, namely a relational DBMS, into such a blockchain framework. As framework, we use the popular Tendermint Core, now part of the Ignite/Cosmos eco-system, which can run both public and permissioned networks and combine it with relational DBMSs as the backend. This results in a "relational blockchain", which is able to run deterministic SQL on a fully replicated relational database. Apart from presenting the integration and its pitfalls, we will carefully evaluate the performance implications of such combinations, in particular, the throughput and latency overhead caused by the blockchain layer on top of the DBMS. As a result, we give recommendations on how to run such a systems combination efficiently in practice.