Computation scales through parallel work hints and proofs that reduce execution load.
Data scaling requires availability, whereas erasure coding allows block-size reduction.
State verification needs full system knowledge, making decentralised scaling the hardest.
Ethereum co-founder Vitalik Buterin outlined a hierarchy that ranks blockchain scalability challenges by difficulty. He placed computation above data and state. His explanation came as Ethereum traded near $2,932 with steady market demand. Buterin said computation scales more easily than data because developers can parallelize processing, use hints, or replace execution with cryptographic proofs.
He explained that data scaling requires availability guarantees, while state scaling remains the hardest challenge because full verification needs complete system information.
The scaling hierarchy in blockchains:
Computation > data > state
Computation is easier to scale than data. You can parallelize it, require the block builder to provide all kinds of "hints" for it, or just replace arbitrary amounts of it with a proof of it.
Data is in the…
— vitalik.eth (@VitalikButerin) January 27, 2026
Ethereum’s price rose 2.41% within 24 hours, while market capitalization reached $353.98 billion. Trading volume fell 4.12% to $26.61 billion. These market signals coincided with renewed discussion about scalability design choices across blockchain systems.
Computation and Data in the Scaling Hierarchy
Buterin described computation as the easiest layer to scale. He said developers can parallelize processing and require block builders to provide hints that reduce workload. He also said cryptographic proofs can replace large portions of computation.
“Computation is easier to scale than data,” Buterin wrote. “You can parallelize it, require the block builder to provide all kinds of ‘hints’ for it, or just replace arbitrary amounts of it with a proof of it.”
He then positioned data as the middle layer in the hierarchy. He explained that data availability remains unavoidable when verification depends on it. Yet he said developers can split data and apply erasure coding techniques. “Data is in the middle,” Buterin wrote. “If an availability guarantee on data is required, then that guarantee is required; there is no way around it.”
He also described Peer Data Availability Sampling as a method that enables flexible scaling. He said nodes with limited capacity can still produce proportionally smaller blocks. This process creates graceful degradation across the network.
“You can do graceful degradation for it,” he wrote. “If a node only has 1/10 the data capacity of the other nodes, it can always produce blocks 1/10 the size.”
Hardest Layer to Scale
Buterin described the state as the most difficult component to scale. He explained that nodes must access the full state to verify even one transaction. Without full state information, verification becomes impossible. “State is the hardest,” Buterin wrote. “To guarantee the ability to verify even one transaction, you need the full state.”
He also explained that replacing the state with tree structures does not remove the need for full state access. Nodes still require complete state data to update the root of the structure. “If you replace the state with a tree and keep the root, you need the full state to be able to update that root,” he wrote.
He acknowledged that some architectural approaches can split state across systems. Yet he said such approaches require fundamental changes and do not offer general-purpose solutions. “There are ways to split it up, but they involve architecture changes,” he wrote. “They are fundamentally not general-purpose.”
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Ethereum Research and Market Context
Buterin linked the hierarchy to broader blockchain design decisions. He argued that developers should replace state with data when possible. He also said developers should replace data with computation if decentralization remains intact.
“Hence, if you can replace state with data, by default you should seriously consider it,” he wrote. “And if you can replace data with computation, by default you should seriously consider it.”
Ethereum researchers have pursued layer-2 solutions such as rollups to offload computation and data commitments. They have also explored PeerDAS to separate data availability from full storage requirements. These approaches aim to scale networks without forcing every node to process all data.
Ethereum’s price movement reflected steady demand during this discussion. The asset climbed from an intraday low near $2,865 and briefly tested the $2,940 zone. Market capitalization rose in line with price, while trading volume declined, suggesting controlled buying rather than aggressive turnover.
The post Vitalik Explains Why Blockchain Scaling Favors Computation appeared first on Cryptotale.
The post Vitalik Explains Why Blockchain Scaling Favors Computation appeared first on Cryptotale.
