Understanding the Three Pillars of Blockchain Scalability: A Perspective by Vitalik Buterin

In his vision of the future of blockchain, Vitalik Buterin has identified a fundamental framework for understanding the scalability of distributed systems. According to Odaily’s report, Buterin’s approach divides scalability challenges into three interconnected components, each with different levels of difficulty and unique solutions.

Computation: The Easiest Layer to Scale

Of the three pillars of blockchain scalability, computation is the most straightforward element to enhance. The available methods for scaling computation are highly diverse, ranging from parallel processing directed by block builders to replacing computationally intensive tasks with modern cryptographic approaches. One of the most promising techniques is using zero-knowledge proofs, which enable verification without the need to run the entire computation process repeatedly. The flexibility of this approach is why computation is not a major bottleneck in scalability.

Data: The Middle Challenge in Blockchain Scalability

Data availability presents a higher level of complexity compared to computation. Reliable blockchain systems require guarantees that all data can be accessed when needed, creating a dilemma between distribution and efficiency. However, various techniques have been developed to overcome this obstacle. Data sharding allows nodes not to store the entire dataset, while erasure coding methods like PeerDAS provide efficient redundancy. The “graceful degradation” approach also enables nodes with limited capacity to participate in block production while maintaining network security.

Status: The Heaviest Bottleneck in System Scalability

When discussing scalability, the blockchain status—namely, the complete record of all accounts and contracts—becomes the most significant obstacle. Every verified transaction requires access to the full state data, even for the simplest operations. Although status is often represented as a Merkle tree structure with only the root stored permanently, updating the root still depends on the presence of comprehensive status data. Efforts to shard the status across different shards face substantial architectural challenges and are difficult to implement universally without compromising the core protocol design.

Optimization Strategies: Priorities for Improving Scalability

From this analysis, Buterin draws practical conclusions about development strategies. If data can replace the function of status without introducing new centralization assumptions, this approach should be a top priority in the scalability roadmap. Similarly, if computation can be optimized to reduce data requirements without compromising security, this strategy is also worth serious consideration. This philosophy reflects Buterin’s understanding that scalability solutions are not just about increasing throughput but about intelligent optimization through the substitution of complementary elements.