Why Rollups Need Data Availability Layers

Let’s face it - Ethereum’s scaling saga reads like a cryptographer’s version of ‘The NeverEnding Story.’ After years of debate, the community settled on rollups as the chosen one to solve the blockchain trilemma. But here’s the catch: most rollups only need Ethereum to do one thing really well - serve as a reliable data availability (DA) layer.

The Execution Integrity Illusion

Both ZK and optimistic rollups promise execution integrity (that fancy term meaning your smart contracts won’t cheat). But there’s a dirty little secret: execution proofs alone don’t guarantee you can actually get your funds out if operators go rogue. For that, we need the full state history to be available - hence the DA requirement.

Optimistic rollups are like that friend who says ‘trust me’ while nervously sweating. They need watchers to catch fraud, which requires full data availability. ZK rollups? More like your math professor - they prove validity cryptographically but still need data availability for practical recovery.

Enter EIP-4844: Ethereum’s DA Upgrade

Currently, rollups use expensive calldata for DA. EIP-4844 introduces ‘blob-carrying transactions’ - basically cheap storage units designed specifically for DA. Here’s why this matters:

• Cost Savings: Blob data is about 80% cheaper than calldata since it’s optimized purely for availability
• Separate Gas Market: Blobs get their own EIP-1559-style fee market, insulating L2s from L1 congestion
• Future-proofing: Sets up infrastructure for full Danksharding down the road

The magic number? Each blob holds ~125KB of data, with targets of 3 blobs per block (380KB total). Not enough to solve all scaling woes yet, but a massive step forward.

Scroll’s Implementation: Circuit Tricks for Blob Verification

In our zkEVM at Scroll, we’ve built a proof-of-concept for verifying blob commitments in-circuit. The challenge? Ethereum uses BLS12-381 curves for blobs while our circuits run on BN254. Our solution:

1. Sample random points on the blob polynomial
2. Verify consistency using Schwartz-Zippel lemma
3. Eat the computational cost of non-native field operations (~28M advice cells)

The result? About 139 seconds per proof on an M1 MacBook - not bad for ensuring mathematical certainty about your data availability.

The Road Ahead

While EIP-4844 is live with the Cancun-Deneb fork, true scaling nirvana requires Danksharding’s data availability sampling. Until then, rollups will juggle between blobs and calldata - or make uncomfortable security tradeoffs with alternative DA layers.

As someone who’s spent too many nights auditing smart contracts, I’ll take any improvement that makes L2s cheaper and more secure. Even if it means explaining polynomial commitments at 2 AM.