Why Data Availability Committees Are a Temporary Scaffold

Modular rollups need cheap, abundant data availability (DA). While Celestia pioneered the market, its capacity is finite. During peak demand, its ~100 KB/s throughput can become a bottleneck, creating a market for alternative DA providers.

• Market Gap: Creates a window for interim solutions before full DAS (Data Availability Sampling) is production-ready.
• Cost Arbitrage: DACs offer ~90% cheaper data posting than Ethereum calldata, a primary rollup cost.

Projects like EigenDA and Avail promise hyperscale DA but require extensive node network bootstrapping and time to achieve robust cryptoeconomic security. DACs provide a production-ready security model today.

• Time-to-Market: Allows rollups like Manta, Aevo, and Lyra to launch immediately.
• Security Model: Relies on a small, known set of reputable entities (e.g., Figment, Nethermind) with slashable stakes, a familiar trade-off for early adopters.

The end-state is a multi-provider DA market where rollups dynamically shop for the cheapest, fastest blob space. DACs are the first competitive entrants in this market, proving demand and defining the service SLA.

• Proof of Concept: Validates the economic model for decentralized DA networks.
• Pressure Valve: Prevents any single DA layer (Celestia, Ethereum) from becoming a monopolistic fee extractor.

DACs explicitly trade maximal decentralization for operational efficiency and lower cost. This is a calculated risk for high-throughput appchains that prioritize user experience and capital efficiency over Byzantine fault tolerance.

• Clear SLAs: Offer ~2s finality versus variable times on base layers.
• Acceptable Risk: For many DeFi and gaming apps, the risk of a coordinated committee failure is outweighed by 10-100x cheaper transaction costs.

DACs like those used by Arbitrum Nova or Polygon Avail's early stage optimize for low cost and high throughput by trusting a small, known set of signers. This creates a single point of failure and regulatory capture risk, undermining the core value proposition of decentralized blockchains.

• Security Model: Relies on honest majority of ~10-20 known entities, not cryptographic guarantees.
• Exit Risk: Users must trust the committee's liveness; a coordinated failure halts chain progress.

Replaces trusted committees with a cryptographically verifiable, permissionless network. Light nodes can probabilistically verify data availability by sampling small, random chunks, enabling secure scaling to MBs per block.

• Architecture: Decouples execution from consensus and DA, creating a modular stack.
• Key Metric: Security scales with the number of light samplers, not a fixed committee size.

Leverages Ethereum's economic security via restaked ETH from EigenLayer. Operators run DA nodes backed by slashed collateral, creating a cryptoeconomically secured network without a new trust layer.

• Security Source: Taps into $10B+ of pooled Ethereum security.
• Integration: Native compatibility with the Ethereum L2 ecosystem (e.g., upcoming Arbitrum, Optimism integrations).

Polygon Avail uses ZK-proofs (KZG commitments) and erasure coding to guarantee data is available. This allows for single-node verification, making it highly efficient for light clients and bridging.

• Core Tech: KZG Polynomial Commitments provide constant-sized proofs for data availability.
• Use Case: Optimized for sovereign rollups and cross-chain unification projects.

Each DAC-operated L2 becomes a siloed liquidity pool. Moving assets between them requires centralized bridges or slow, expensive L1 withdrawals, crippling composability.

• Bridge Risk: ~$2.8B has been stolen from cross-chain bridges, many relying on multisig/DAC models.
• Developer Friction: Apps must deploy and maintain separate codebases for each DAC environment.

The end-state is a competitive market of permissionless DA layers (Celestia, EigenDA, Avail, Ethereum Danksharding) where rollups choose based on cost, throughput, and security profile. DACs are the training wheels.

• Market Effect: Drives DA costs toward marginal cost of bandwidth and storage.
• Winner: The ecosystem with the strongest credible neutrality and lowest friction for developers.