  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.
