Quantifying Smart Contract Network Demand
Such networks, referred to by some as ‘Blockchain 3.0’, attempt to iterate on both Bitcoin and Ethereum’s core functionalities, seeking to provide marked improvements in scalability, interoperability, and privacy. While many are yet to debut, a significant number have had functioning mainnets for some time, which has led to quantifiable comparisons between these emergent networks and Ethereum.
While all on-chain metrics have their flaws and are generally unreliable in isolation, certain indicators can be gamed more easily than others. This is especially true of networks where computational costs and fees are negligible, making it inexpensive to flood them with transactions and even engage in spam or Denial-of-Service-like behavior. Nowhere are such phenomena more emphasized than on the EOS network, which has been subject to robust criticism regarding the degree of its real transaction demand, as determined by economic value. One recent study, for instance, claimed that 95% of transactions on the network between Oct. 2019 – Jan. 2020 were due to the EIDOS token airdrop which is now of near-zero market value and was widely cited as causing large-scale congestion. Similar criticisms have been levied at other high-throughput networks with minimal fees such as Tron among others.
In an attempt to filter-out low-value activity such as this, some in the industry have suggested quantifying network demand by the aggregate cost that market participants are willing to pay validators. To this end, Chris Burniske, a partner at the cryptoasset investment firm, Placeholder, recently highlighted their work, in measuring the total amount of fees paid to miners on Ethereum relative to other networks, positing that this metric serves as a proxy for market demand. Unlike other metrics such as total transfer counts or the number of addresses and accounts, all of which have radically different associated costs across different architectures, the aggregate fees paid to miners, or generalized network validators in other cases, is supposedly a true reflection of the collective costs that the market is willing to expend for access to block space and computation. Such analysis ultimately reflects an incredibly stark difference between such demand for Ethereum compared to other networks. While Ethereum currently extracts $345,032 in fees per day on a 14-day average basis, Tezos, the next highest registers at just $152, representing a 2270-fold difference, while other networks such as Lisk, Ethereum Classic, Cardano and Neo, collectively account for just $302.
Log 1 Year Chart of Network Fees per 24 hours in USD (14 Day Rolling Average) on Ethereum, Tezos, Lisk, Ethereum Classic, Cardano and Neo.
Source: Coin Metrics
Moreover, Ethereum’s lead on this basis may be even larger, given that, according to a recent study, 82% of Tezos transactions are due to endorsement transactions, namely those involved in consensus via staking rather than demand for applications or use cases beyond network consensus. It should be noted that such analysis inevitably excludes networks like EOS and Tron due to their alternative architectures and our primary data source, Coin Metrics in this instance, does not capture other emergent networks such as Cosmos Hub, Qtum, Zilliqa, and others.
Overall then, while Burniske and Placeholder’s approach to measuring smart contract network demand inevitably excludes certain networks from such comparative analysis, the fundamental approach of measuring market demand via aggregated network fees is in our view a sound one for its ability to measure market demand quantifiably and accurately.