On-chain Atomic Batching vs Off-chain Batching (Rollup)

Native Finality & Composability: Transactions settle atomically on the base layer (e.g., Solana, Sui). This enables trustless cross-program calls and is critical for high-frequency DeFi arbitrage and complex NFT minting workflows.

No External Security Assumptions: Security inherits directly from the underlying L1 consensus. There's no reliance on a separate prover network or multi-sig bridge, eliminating a major attack vector for protocols like Jupiter and Raydium.

Scalability Bottleneck: Throughput is capped by base layer consensus. Solana's ~5,000 TPS is a hard limit for all applications, leading to congestion during peaks.

Higher Base Layer Costs: Every transaction pays L1 gas fees. During network stress, this makes high-volume, low-value operations (e.g., micro-payments, per-action gaming) economically unviable compared to rollup solutions.

Exponential Scalability: Executes thousands of transactions off-chain and posts compressed data to L1. ZK-Rollups like StarkNet and zkSync can achieve 10,000+ TPS, ideal for mass-market social apps and gaming.

Dramatically Lower User Fees: Costs are amortized across the entire batch. On Optimism and Arbitrum, simple swaps can cost <$0.01, enabling sustainable business models for high-frequency applications.

Delayed Finality & Fragmentation: Users face soft confirmation from the sequencer and a challenge period (7 days for Optimistic Rollups) or prover time (minutes for ZK). This breaks atomic composability with L1 and other rollups, a key challenge for cross-chain DeFi.

Complex Trust Assumptions: Relies on sequencer liveness and honest majority assumptions for data availability. Validium solutions (e.g., Immutable X) introduce additional DA committee risk, trading off some security for lower cost.

Guaranteed atomic execution: All transactions in a batch succeed or fail together, preventing partial failures. This is critical for DeFi composability (e.g., arbitrage, multi-step swaps) and NFT minting where dependencies are absolute. Native security: Inherits the full security and finality of the underlying L1 (e.g., Ethereum), with no additional trust assumptions for sequencing.

Higher gas costs and latency: Each batch is an L1 transaction, incurring high base fees and competing for block space. This limits batch frequency and size, capping scalability. Sequencer centralization pressure: To be economically viable, sequencing often consolidates to a single entity to amortize L1 costs, creating a potential single point of failure or censorship.

Massive scalability & low user fees: Executes and batches thousands of transactions off-chain before posting compressed data to L1. Enables > 2,000 TPS and <$0.01 fees for applications like high-frequency gaming and micro-payments. Flexible sequencing: Can support decentralized sequencer sets (e.g., Espresso, Astria) or fast, centralized sequencers for optimal performance.

Added trust and complexity: Introduces a sequencer as a new trust component for liveness. Users rely on fraud proofs (Optimistic) or validity proofs (ZK) for security, which have different finality delays (7 days vs ~20 mins). Protocol risk: Smart contract bugs in bridge or proof verification contracts (e.g., Wormhole, Nomad incidents) present a significant attack vector not present in pure on-chain execution.