Why Decentralized Storage Is Critical for Infrastructure Data

Centralized RPC providers like Alchemy and Infura are single points of failure for querying blockchain state. Their centralized data pipelines create latency, censorship risk, and vendor lock-in for protocols managing $100B+ in TVL.

• Centralized Downtime: A single provider outage can cripple dApp frontends.
• Data Sovereignty: Providers can censor or manipulate query results.
• Cost Scaling: Pricing models become prohibitive for data-intensive apps like on-chain analytics.

Protocols like The Graph and Subsquid decentralize the data indexing layer, allowing anyone to run a node that serves queries. This creates a competitive, permissionless market for blockchain data.

• Censorship Resistance: No single entity can block access to historical or real-time data.
• Performance: A distributed network can reduce query latency by routing to the nearest node.
• Data Integrity: Cryptographic proofs, like The Graph's attestations, can verify query correctness.

The rise of zk-proofs and optimistic fraud proofs (via EigenDA, Celestia) is creating a new paradigm: storing only state diffs and recalculating history on-demand. This demands a storage layer that can serve provable data blobs for re-execution.

• Data Availability: Rollups like Arbitrum and Optimism need cheap, reliable storage for transaction data.
• Proof Generation: zkEVMs like Polygon zkEVM require fast access to historical state for proof creation.
• Modular Future: Separating execution, settlement, and data availability makes decentralized storage a foundational pillar.

Arweave provides permanent, low-cost storage via a blockchain-structured data layer. Its endowment model guarantees one-time payment for eternal storage, making it ideal for archiving critical infrastructure data.

• Permanence: Data is stored across a decentralized network with cryptoeconomic guarantees.
• Cost Predictability: No recurring fees, crucial for long-term data budgeting.
• Use Cases: Hosting frontends, storing protocol archives, and securing NFT metadata for projects like Solana.

Applications like UniswapX, Across, and LayerZero rely on unified state across multiple chains. Centralized oracles and relayers become trusted intermediaries, undermining the security model of $50B+ in bridged value.

• Oracle Risk: A malicious or faulty oracle can corrupt cross-chain state synchronization.
• Data Consistency: Ensuring all chains see the same canonical state is a massive coordination problem.
• Speed vs. Security: Fast bridges often sacrifice decentralization, creating systemic risk.

Decentralizing the sequencer layer (e.g., Espresso, Astria) and prover networks (e.g., =nil; Foundation) moves critical off-chain computation into a trust-minimized framework. Their operational data must be stored verifiably.

• Sequencer Decentralization: Prevents MEV extraction and censorship by a single entity.
• Prover Markets: Enable competitive, cost-effective proof generation for zk-rollups.
• Data Logging: All sequencing and proving actions must be logged to a neutral data layer for audit and dispute resolution.

Infrastructure data (RPC calls, sequencer states, bridge proofs) is currently routed through centralized gateways like Infura and Alchemy. This creates a single point of failure and censorship, undermining the decentralization of the L1/L2s they serve.

• Single Point of Truth: A compromised or coerced provider can censor or spoof data for entire chains.
• Data Integrity Risk: No cryptographic proof that the served data matches the canonical chain state.

Current infrastructure emits logs and states that are not persistently stored or easily auditable on-chain. This creates a black box for critical events like cross-chain messaging or sequencer downtime, making fraud proofs impossible.

• Unprovable Claims: Users must trust that a bridge's off-chain attestation is correct.
• No Historical Audit Trail: Investigating an exploit or failure relies on the goodwill of a centralized entity to provide logs.

Projects like The Graph index data, but the raw data itself remains in centralized storage. This creates silos where the cost and permanence of data are at the mercy of a single provider's business model, leading to link rot and protocol fragility.

• Permanence Risk: API endpoints and hosted data can disappear, breaking dApp frontends and smart contract logic.
• Vendor Lock-In: High switching costs and re-indexing times create systemic fragility.

Centralized cloud storage (AWS S3) appears cheap and fast, but its economic model is antithetical to Web3. Egress fees and geopolitical zoning create unpredictable costs and latency, making reliable global infrastructure impossible to budget for.

• Hidden Costs: Exploding egress fees can bankrupt a protocol during high-traffic events.
• Performance Inconsistency: Data locality issues cause >1s latency spikes for users in unsupported regions.

While pioneers, they solve for generic file storage, not infrastructure data verifiability. Their models lack the real-time queryability, low-latency updates, and structured data primitives needed for chain state proofs and RPC responses.

• Slow Finality: Arweave's ~2-minute block time is too slow for real-time state verification.
• Complex Retrieval: Filecoin's retrieval market adds latency and uncertainty unsuitable for dApp backends.

The solution is a dedicated verifiable data availability (DA) layer for infrastructure, akin to Celestia for rollups but for logs and states. It must offer cryptographic inclusion proofs, sub-second updates, and permissionless publishing to replace trust with verification.

• Proof-Centric Design: Every data payload must have a verifiable commitment posted to a base layer (e.g., Ethereum).
• Universal Access: Anyone can publish/retrieve data, breaking the gateway oligopoly.