Monolithic DA vs Modular DA

Single-stack sovereignty: Data availability is bundled with execution and consensus (e.g., Ethereum L1, Solana). This provides atomic composability and a unified security model. Ideal for general-purpose L1s prioritizing developer simplicity and maximal security.

Throughput is inherently limited by the base layer's block size and speed. Ethereum's ~80 KB/s DA throughput creates a bottleneck for high-volume rollups. This forces trade-offs between decentralization, security, and scale, often leading to high L1 gas fees for data posting.

Decoupled data layer (e.g., Celestia, Avail, EigenDA) designed solely for high-throughput data ordering and availability proofs. Enables 10,000+ TPS for rollups by separating concerns. Use case: High-throughput app-chains and rollups needing low, predictable data costs.

Introduces bridging complexity between execution and DA layers, breaking atomic composability. Security is sourced separately (e.g., via restaking with EigenLayer or a dedicated validator set), which differs from Ethereum's battle-tested consensus. Adds operational overhead for cross-domain applications.

Unified execution and data layer: Tight integration (e.g., Ethereum's L1, Solana) provides deterministic finality and low latency between consensus and data posting. This matters for high-frequency DeFi where settlement and data availability must be atomic to prevent front-running.

Security is the base layer's security: Data availability is secured by the same validators and economic stake securing consensus (e.g., Ethereum's ~$40B+ staked ETH). This matters for high-value, trust-minimized bridges and sovereign chains that cannot compromise on liveness guarantees.

Specialized, high-throughput data layers: Dedicated networks like Celestia (100 MB/s blockspace) and EigenDA (10-100 MB/s) decouple data from execution, offering ~$0.001 per MB data posting costs. This matters for high-throughput L2s (Arbitrum, Optimism) and modular app-chains needing predictable, low-cost data.

Choice of security models: Developers can choose between economic security (Celestia), restaked security (EigenDA via EigenLayer), or validium proofs (zkPorter). This matters for niche app-chains and gaming rollups that need to optimize for specific throughput, cost, and trust assumptions.

Limited, expensive blockspace: On Ethereum, DA competes with execution for ~15-20 MB/minute, leading to high and volatile calldata costs (>$1,000 per MB during peaks). This matters for scaling startups and high-volume dApps where cost predictability is critical for unit economics.

New security and trust assumptions: Modular DA layers have smaller, independent validator sets (e.g., Celestia's ~$2B market cap vs. Ethereum's ~$400B). This matters for institutional DeFi and cross-chain protocols where the strongest possible liveness guarantees are non-negotiable.

Integrated Security & Simplicity: Data availability is secured by the same validators as execution (e.g., Ethereum L1, Solana). This eliminates cross-layer trust assumptions, simplifying security modeling and reducing integration complexity for developers.

Cost & Throughput Bottleneck: DA capacity is limited by the base layer's consensus. On Ethereum, this leads to high blob costs (~$0.01-$0.10 per blob) and constrained TPS for rollups, directly impacting user transaction fees.

Scalability & Cost Efficiency: Dedicated DA layers like Celestia, Avail, and EigenDA offer orders-of-magnitude higher throughput (e.g., Celestia's ~100 MB blocks) and lower costs (< $0.001 per MB), enabling high-throughput, low-fee L2s and rollups.

Added Complexity & New Trust Assumptions: Introduces a separate security layer. Rollups must trust or verify the modular DA network's consensus and data availability proofs (e.g., Data Availability Sampling), increasing protocol and client complexity.