Evaluating Blockchain Platforms: A Comparative Analysis

Blockchain technology has enabled the emergence of a new kind of distributed system. It provides mechanisms in which decentralized transactions and operations are secure, without the need to trust a mediating third-party as it is common in server-centric centralized systemsFootnote 1 [1, 2]. Due to its origins linked to cryptocurrencies, blockchain has been mostly applied to financial applications. However, in recent years it is increasingly applied to other fields [3]. A specially interesting application is the emergence of new forms of decentralized governance which are mediated by a blockchain. These blockchain-enabled organizations are known as Decentralized Autonomous Organizations (DAOs), and take benefit of the affordances of blockchain infrastructure to enable e.g. transparent decision processes, formalized rules, automation of certain operations, or alleged decentralization of power [4].

The blockchain field has attracted a broad range of experts and enthusiasts [5], currently with a majority belonging to the fields of Computing and Finance, and focused on new financial applications, e.g. the booming DeFi fieldFootnote 2. Some of these projects chose to rely on DAOs for their governance. Thus, the project’s online community may use the DAO embedded decision-making mechanisms to vote proposals and organize their tasks. In order to meet this demand, several platforms have recently appeared to provide DAOs as-a-service, that is, deploying DAOs in a public blockchain and facilitating community interactions through them. These platforms have reduced the technical knowledge required to operate through a DAO, and thus thousands of people are now interacting within hundreds of DAO communities.

This new phenomenon can be followed on the Internet, particularly, through ‘grey literature’ including technical reports, blogs, social media posts, etc. Research literature has covered it mostly with theoretical works [4, 6, 7], although some empirical works have been slowly emerging. We can highlight qualitative research such as an ethnographic account of the first popular DAO [8], a comprehensive study understanding the imaginaries behind DAOs [9], or a content analysis of grey literature on three popular DAOs to understand how are they governed [10]. In [11] we can find an overview of DAOs, DAO platforms and DAO visualization tools, and a analysis of the evolution of one popular DAO looking at the time series of metrics such as the number of users and actions performed in the DAO. Recently, a study analyzed how affected on DAO activities the increases in the costs of using the Ethereum blockhain that took place in the second half of 2020 [12].

In this paper, we will contribute to the growing stream on literature on the topic by providing a statistical analysis of three of the main DAO platforms (Aragon, DAOstack and DAOhaus) in terms of growth, activity, voting system and funds.

The article proceeds as follows: Section 2 introduces the main concepts related to blockchain, Ethereum and DAOs. In Section 3, we review the three DAO platforms that we are going to analyze in this work. Section 4 compares the three main DAO platforms in terms of growth, activity, voting system and funds. Section 5 proceeds to discuss the main findings, while Section 6 finishes with some concluding remarks, including the limitations of our work.

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