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A New Perspective on Layered Understanding of Blockchain Scalability: Vitalik Buterin's Viewpoint
Vitalik Buterin recently elaborated on his layered understanding of blockchain scalability. According to Odaily’s report, the Ethereum co-founder divides the complexity of scaling blockchain systems into three levels, from easiest to hardest: computation, data, and state. This framework offers a new perspective for understanding the current bottlenecks in blockchain systems.
Buterin emphasizes that the varying difficulty in understanding blockchain scalability is key to deepening knowledge in this field. He points out that the computation layer is relatively easier to optimize, and developers can achieve scalability through various methods, including leveraging “tips” provided by block producers for parallel processing or replacing complex on-chain calculations with cryptographic solutions like zero-knowledge proofs. These approaches have been validated in practice and show promising scalability potential.
Optimization Opportunities and Technical Challenges at the Data Layer
Data scalability is positioned in the middle, with moderate difficulty but still requiring innovation. The key at this layer is ensuring data availability without overburdening network nodes. To achieve this balance, industry practices include data sharding, erasure coding, and other technical solutions. The PeerDAS protocol is a representative example, allowing low-capacity nodes to participate in block production without storing the full data. Additionally, designing for “graceful degradation” is also important—meaning that even if some nodes have limited data processing capabilities, the entire system can still operate normally.
The Fundamental Challenge of State Expansion
State scalability is the most difficult challenge. Buterin points out that verifying any individual transaction requires nodes to have complete state information. Even if the state is abstracted into a tree structure, retaining only the root hash, updating this root still depends on accessing and computing the entire state. Existing state sharding solutions often require significant architectural reforms, and their general applicability and feasibility face serious tests.
Strategic Thinking on Scalability Priorities
Based on this layered understanding, Buterin proposes an important principle for optimization strategies. If data mechanisms can replace the role of state without introducing new centralization assumptions, this should be the developers’ top priority. Similarly, if computation can substitute for data functions without compromising decentralization, such solutions are also worth considering. This prioritization reflects a steadfast commitment to protecting the essence of network decentralization—minimizing node state maintenance burdens while ensuring security.
This layered understanding provides theoretical guidance for current and future blockchain scaling solutions, helping developers and researchers clarify their direction amid numerous technical options.