Blockchain has come a long way — a system that was initially proposed specifically for cryptocurrencies is now being adapted and adopted as a general-purpose transactional system. As blockchain
evolves into another data management system, the natural question is how it compares against distributed database systems. Existing works on this comparison focus on high-level properties, such as
security and throughput. They stop short of showing how the underlying design choices contribute
to the overall differences. Our work fills this important gap and provides a principled framework for
analyzing the emerging trend of blockchain-database fusion.
We perform a twin study of blockchains and distributed database systems as two types of transactional systems. We propose a taxonomy that illustrates the dichotomy across four dimensions,
namely replication, concurrency, storage, and sharding. Within each dimension, we discuss how the
design choices are driven by two goals: security for blockchains, and performance for distributed
databases. To expose the impact of different design choices on the overall performance, we conduct
an in-depth performance analysis of two blockchains, namely Quorum and Hyperledger Fabric, and
two distributed databases, namely TiDB, and etcd. Lastly, we propose a framework for back-of-theenvelope performance forecast of blockchain-database hybrids.