Why Batch Processing is the Unsung Hero of Scalable Airdrop Claims

Airdrop claims are a denial-of-service attack that users pay for. Every individual claim transaction competes for block space, spiking gas fees and degrading network performance for all other applications.

Batch processing is the only viable scaling solution for this specific problem. It consolidates thousands of individual user signatures into a single on-chain transaction, decoupling claim activity from mainnet congestion. This is the same principle used by rollups like Arbitrum and Optimism for scaling execution.

The proof is in the failed launches. The Ethereum Name Service (ENS) airdrop in 2021 congested the Ethereum mainnet, with gas fees exceeding 7,000 gwei. In contrast, LayerZero's recent airdrop utilized a merkle claim model that offloaded verification cost, demonstrating the architectural shift.

Single-User Claims are Economically Irrational. Each individual claim transaction competes for block space, paying a base gas fee. For a 1M user airdrop on Ethereum, this translates to 1M separate L1 calldata writes, a cost structure that scales linearly and catastrophically.

Batching Flattens the Cost Curve. A single batch transaction submits a Merkle root, compressing verification for all users into one on-chain operation. This changes the cost model from O(n) to O(1) for the core claim logic, a fundamental shift in scalability.

The Proof is in the Pudding. Protocols like Optimism's Airdrop #1 and Arbitrum used Merkle-based batching, enabling distribution to hundreds of thousands of wallets. In contrast, non-batched distributions on congested chains like Solana during the Jito airdrop caused network-wide RPC failure and $2M in lost user funds to failed transactions.

Batching is a Prerequisite for Cross-Chain Claims. To distribute tokens from a source chain like Ethereum to users on Arbitrum, zkSync, and Polygon, you batch proofs per destination. This is the same architectural pattern used by intent-based bridges like Across and LayerZero for efficient cross-chain message passing.

Airdrops are infrastructure stress tests. A successful claim requires a user to sign and broadcast a transaction, creating a massive, synchronized demand spike that clogs mempools and inflates gas fees for the entire network.

Batch processing decouples claim from execution. Protocols like EigenLayer and zkSync use Merkle proofs and claim contracts, allowing users to submit a permissionless proof. A relayer then batches thousands of these off-chain signatures into a single on-chain transaction.

This shifts cost and complexity. The gas burden moves from the user to the project or relayer, which can optimize timing and pay bulk rates. Users experience near-instant, feeless claims while the settlement occurs in a single, efficient transaction.

Evidence: The Starknet airdrop processed over 45 million STRK claims. Without batched claiming via Merkle distributions, the resulting gas war would have made the airdrop economically worthless for most recipients.

Merkle roots enable off-chain verification. A single 32-byte hash on-chain proves the validity of millions of user claims, compressing massive datasets into a single state commitment.

Aggregators like CowSwap and UniswapX are natural batching agents. Their existing infrastructure for order settlement is repurposed to submit bundled claim transactions, amortizing gas costs across thousands of users.

This creates a two-tiered system. Users sign off-chain messages (intents), while a designated relayer handles the on-chain execution, separating proof from payment.

Evidence: The Arbitrum airdrop processed over 625,000 claims in its first day; a naive per-user transaction model would have congested the network and cost tens of millions in gas.

L2s are not magic. They batch transactions for cheaper settlement, but each airdrop claim is still a unique state update. A million claims require a million L2 transactions, creating a predictable gas war.

Batch processing is the real scaling primitive. Protocols like EigenLayer and AltLayer process claims off-chain, generating a single validity proof for the entire set. This reduces the on-chain footprint from N transactions to one.

The comparison is batch vs. rollup. A rollup batches execution, but a claim batch processes logic. This is the difference between compressing traffic and building a highway.

Evidence: The Starknet airdrop in 2024 processed ~1.3 million claims. Despite being on an L2, it caused sustained network congestion and fee spikes for hours, demonstrating the inherent limit of per-transaction models.

Batch processing is the core primitive for scaling airdrop claims. It aggregates thousands of individual claim transactions into a single on-chain proof, reducing gas costs by over 95% and eliminating network congestion. This is the same principle used by rollups like Arbitrum and Optimism for L2 scaling.

The real innovation is cross-chain execution. Protocols like LayerZero and Wormhole enable batch proofs to be verified on a destination chain. A user signs an intent on Ethereum, and a solver executes the claim on Arbitrum via a cheap batch transaction, settling the final state back to the user's origin chain.

This creates intent-based airdrops. Users express a desired outcome (e.g., 'claim my ARB tokens to my Polygon wallet'), and decentralized solvers compete to fulfill it via the most efficient path across chains like Avalanche or Base. This mirrors the architecture of UniswapX and Across Protocol.

The evidence is in the gas. A traditional 10,000-user claim event can cost over 50 ETH in gas. A batched claim via a zk-proof, as implemented by projects using Succinct Labs' SP1, reduces this to a single transaction costing less than 0.5 ETH, making large-scale distributions economically viable.