Bitcoin PoW vs Ethereum PoS: Control Spread

Decentralized physical security: Hashrate is geographically distributed and requires specialized hardware (ASICs), making 51% attacks astronomically expensive (>$20B+ to attack). This matters for sovereign-grade store of value and final settlement where censorship resistance is paramount.

Algorithmic, unchangeable issuance: The 21M coin cap and halving schedule are enforced by consensus, not governance votes. This matters for long-term capital allocation and institutional treasury reserves where predictable scarcity is a non-negotiable feature.

High-throughput execution layer: Supports ~15-45 TPS on L1 and 1000s+ via L2 rollups (Arbitrum, Optimism, zkSync). Native smart contract capability enables complex DeFi (Uniswap, Aave) and applications. This matters for active finance, NFTs, and scalable dApps requiring low-cost, fast transactions.

~99.95% lower energy use than PoW, addressing ESG concerns. On-chain governance via proposals (EIPs) allows for protocol upgrades (e.g., EIP-1559, The Merge). This matters for enterprise adoption, regulatory compliance, and iterative development where adaptability and sustainability are key.

Mining-based security: Control is spread across globally distributed miners competing with ASIC hardware. This creates a high physical barrier to entry and makes geographic or political coordination attacks extremely difficult. It's ideal for maximizing censorship resistance for high-value, immutable settlement.

Energy-intensive consensus: Security is backed by real-world energy expenditure (~150 TWh/yr). This creates immense economic finality but results in high, ongoing operational costs and environmental externalities. This trade-off is justified for a store-of-value asset but prohibitive for high-throughput applications.

Stake-based security: Control is proportional to staked ETH (32 ETH per validator). This reduces energy use by >99.95% and lowers the barrier to participation, enabling broader validator set distribution (1M+ validators). It's optimal for scalable dApp platforms requiring sustainable, high-frequency finality.

Liquid staking derivatives (LSDs): Platforms like Lido (LDO) and Rocket Pool (RPL) create pooling, which can lead to concentration risk (e.g., Lido controls ~29% of staked ETH). Reliance on a smaller set of node operators and client software diversity are active concerns. This model prioritizes efficiency and yield over maximalist decentralization.

Mining-based distribution: Control is spread across competing mining pools (e.g., Foundry USA, Antpool) based on hash rate contribution. No single entity can dictate rules without overwhelming >51% of global hash power.

This matters for protocols requiring maximal security and censorship resistance for high-value settlement, like storing treasury reserves or cross-chain asset bridges.

Hard fork is the only upgrade path: Protocol changes (e.g., Taproot) require near-unanimous miner and node operator consensus, leading to slow evolution.

This matters for teams that need predictable, static base layers but is a constraint for applications requiring frequent feature updates or scalability tweaks.

Validator-based governance: Control is proportional to staked ETH (32 ETH per validator). Large entities like Lido (LDO), Coinbase (CBETH), and Rocket Pool (rETH) operate significant validator shares, centralizing influence.

This matters for protocols integrating with DeFi and smart contract ecosystems where governance participation and upgrade agility are critical, despite higher centralization risks.

Frequent, coordinated upgrades: The core developer team (EF) and client teams (Prysm, Lighthouse) can push upgrades like Dencun via social consensus, enabling rapid scaling (e.g., EIP-4844 for blobs).

This matters for application developers building on L2s (Arbitrum, Optimism, zkSync) who benefit from lower fees and new primitives, but must manage upgrade complexity and smart contract risk.