Vitalik's New Scalability Theory: Why is Computation Easily Scalable but State Difficult to Break? How Can Ethereum Break Through?

On January 27th, Ethereum co-founder Vitalik Buterin announced a brand new blockchain scalability framework. He used the term “hierarchical structure” to explain why the scalability of different technical components varies greatly, and pointed out that state is the true bottleneck for Ethereum’s expansion. This model provides a clear technical roadmap for understanding Ethereum’s long-term scalability path.

Three-layer Model: Why Is Scalability Inconsistent?

Vitalik divides blockchain scalability difficulty into three levels:

The core insight of this layered approach is: the scalability difficulty of each layer depends on its constraints on decentralization. Computation can be outsourced, data can be distributed, but state must be verified by the entire network.

Computation Layer: Mature Solutions Available

Computation is the easiest part to scale. Vitalik points out that scalability can be improved through:

• Parallel execution: multiple computations happening simultaneously rather than sequentially
• Zero-knowledge proofs: cryptographic proofs replacing large on-chain computations
• Off-chain computation: outsourcing transaction processing to external systems, submitting only the results for main chain verification

This is also the foundational logic behind most current Layer 2 solutions. Rollups, by executing transactions off-chain and submitting compressed results to the Ethereum mainnet, have already achieved hundreds of times throughput improvement.

Data Layer: PeerDAS Brings New Opportunities

Compared to computation, data scalability is slower. Blockchains must ensure key data can be verified and accessed, which directly limits scalability. However, according to recent information, with the introduction of data distribution technologies like PeerDAS, Ethereum is reducing the storage and bandwidth pressure on nodes.

What does this mean? Through data sharding and erasure coding, different nodes can verify only parts of the data instead of the entire dataset. This supports more users and higher data demands while maintaining decentralization and lowering hardware requirements.

State Layer: The Real Bottleneck

State is the true bottleneck for scalability. Each node must verify and store the entire network state (account balances, smart contract data, etc.), and the continuous growth of state size increases hardware requirements. In the long run, it may also pose centralization risks.

To address this, Vitalik proposed the idea of “ascending the hierarchy”: replacing state with computation and data as much as possible. Specific technical solutions include:

• Rollups: moving most state off-chain, only storing necessary verification data on the main chain
• Sharding: distributing data and state load across different shards, each handling a subset of the state
• Zero-knowledge proofs: reducing on-chain execution costs by cryptographically proving correctness of state without revealing all data

It’s worth noting that recent information mentions Vitalik has abandoned an old view from 2017. He now believes that the maturity of ZK-SNARKs and other zero-knowledge technologies allows users to verify the correctness of on-chain state without replaying all historical transactions. This further confirms the critical role of zero-knowledge proofs in state verification.

Guidance for Developers and the Ecosystem

This layered model offers direct and clear guidance for developers:

Reduce unnecessary on-chain state, rely more on proofs and verifiable data, and shift complexity to higher layers. In other words, avoid having the main chain store and verify all data, instead letting Layer 2 and other scaling solutions handle that part.

Recent information indicates that early Layer 2 solutions like Plasma are experiencing a revival, integrating new technologies such as zero-knowledge proofs. This shows that Vitalik’s theoretical framework is actively guiding practical ecosystem development.

Summary

Vitalik’s three-layer scalability model provides a new perspective for understanding Ethereum’s scalability roadmap. It clearly highlights the fundamental pattern: computation is easiest to scale, data is intermediate, and state is the most challenging. It also proposes the “ascending hierarchy” approach as a solution.

The value of this model lies in its not just listing technologies but offering a systematic design framework. Developers can optimize architecture accordingly, and ecosystem projects can choose their scalability directions based on it. Coupled with the maturity of ZK technologies and new solutions like PeerDAS, Ethereum is attempting to strike a new balance between performance, cost, and decentralization. This process won’t be instantaneous, but the direction is now sufficiently clear.